{"id":31058,"date":"2021-11-12T01:52:35","date_gmt":"2021-11-12T01:52:35","guid":{"rendered":"https:\/\/www.dumpsbase.com\/freedumps\/?p=31058"},"modified":"2021-11-12T01:52:38","modified_gmt":"2021-11-12T01:52:38","slug":"real-databricks-certified-professional-data-scientist-dumps-with-actual-questions","status":"publish","type":"post","link":"https:\/\/www.dumpsbase.com\/freedumps\/real-databricks-certified-professional-data-scientist-dumps-with-actual-questions.html","title":{"rendered":"Real Databricks Certified Professional Data Scientist Dumps With Actual Questions"},"content":{"rendered":"\n<p>Why choose to pass Databricks Certified Professional Data Scientist certification exam? It assesses the understanding of the basics of machine learning, the steps in the machine learning lifecycle, the understanding of basic machine learning algorithms and techniques, and the understanding of the basics of machine learning model management. DumpsBase wants to help more candidates complete their Databricks Certified Professional Data Scientist exam, so\u00a0 real Databricks Certified Professional Data Scientist dumps are released by the top team with the actual Databricks Certified Professional Data Scientist dumps questions. Practicing Databricks Certified Professional Data Scientist exam dumps Q&amp;As can be your best preparation materials of passing Databricks Certified Professional Data Scientist certification exam.<\/p>\n<h2>Check <span style=\"background-color: #ffff00;\">Databricks Certified Professional Data Scientist free dumps below<\/span> To Check The Real Dumps<\/h2>\n<script>\n\t  window.fbAsyncInit = function() {\n\t    FB.init({\n\t      appId            : '622169541470367',\n\t      autoLogAppEvents : true,\n\t      xfbml            : true,\n\t      version          : 'v3.1'\n\t    });\n\t  };\n\t\n\t  (function(d, s, id){\n\t     var js, fjs = d.getElementsByTagName(s)[0];\n\t     if (d.getElementById(id)) {return;}\n\t     js = d.createElement(s); js.id = id;\n\t     js.src = \"https:\/\/connect.facebook.net\/en_US\/sdk.js\";\n\t     fjs.parentNode.insertBefore(js, fjs);\n\t   }(document, 'script', 'facebook-jssdk'));\n\t<\/script><script type=\"text\/javascript\" >\ndocument.addEventListener(\"DOMContentLoaded\", function(event) { \nif(!window.jQuery) alert(\"The important jQuery library is not properly loaded in your site. Your WordPress theme is probably missing the essential wp_head() call. You can switch to another theme and you will see that the plugin works fine and this notice disappears. If you are still not sure what to do you can contact us for help.\");\n});\n<\/script>  \n  \n<div  id=\"watupro_quiz\" class=\"quiz-area single-page-quiz\">\n<p id=\"submittingExam5865\" style=\"display:none;text-align:center;\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\"><\/p>\n\n<div class=\"watupro-exam-description\" id=\"description-quiz-5865\"><\/div>\n\n<form action=\"\" method=\"post\" class=\"quiz-form\" id=\"quiz-5865\"  enctype=\"multipart\/form-data\" >\n<div class='watu-question ' id='question-1' style=';'><div id='questionWrap-1'  class='   watupro-question-id-199203'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>1. <\/span>You are creating a regression model with the input income, education and current debt of a customer, what could be the possible output from this model.<\/div><input type='hidden' name='question_id[]' id='qID_1' value='199203' \/><input type='hidden' id='answerType199203' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199203[]' id='answer-id-798780' class='answer   answerof-199203 ' value='798780'   \/><label for='answer-id-798780' id='answer-label-798780' class=' answer'><span>Customer fit as a good<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199203[]' id='answer-id-798781' class='answer   answerof-199203 ' value='798781'   \/><label for='answer-id-798781' id='answer-label-798781' class=' answer'><span>Customer fit as acceptable or average category<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199203[]' id='answer-id-798782' class='answer   answerof-199203 ' value='798782'   \/><label for='answer-id-798782' id='answer-label-798782' class=' answer'><span>expressed as a percent, that the customer will default on a loan<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199203[]' id='answer-id-798783' class='answer   answerof-199203 ' value='798783'   \/><label for='answer-id-798783' id='answer-label-798783' class=' answer'><span>1 and 3 are correct<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199203[]' id='answer-id-798784' class='answer   answerof-199203 ' value='798784'   \/><label for='answer-id-798784' id='answer-label-798784' class=' answer'><span>2 and 3 are correct<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-2' style=';'><div id='questionWrap-2'  class='   watupro-question-id-199204'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>2. <\/span>What type of output generated in case of linear regression?<\/div><input type='hidden' name='question_id[]' id='qID_2' value='199204' \/><input type='hidden' id='answerType199204' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199204[]' id='answer-id-798785' class='answer   answerof-199204 ' value='798785'   \/><label for='answer-id-798785' id='answer-label-798785' class=' answer'><span>Continuous variable<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199204[]' id='answer-id-798786' class='answer   answerof-199204 ' value='798786'   \/><label for='answer-id-798786' id='answer-label-798786' class=' answer'><span>Discrete Variable<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199204[]' id='answer-id-798787' class='answer   answerof-199204 ' value='798787'   \/><label for='answer-id-798787' id='answer-label-798787' class=' answer'><span>Any of the Continuous and Discrete variable<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199204[]' id='answer-id-798788' class='answer   answerof-199204 ' value='798788'   \/><label for='answer-id-798788' id='answer-label-798788' class=' answer'><span>Values between 0 and 1<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-3' style=';'><div id='questionWrap-3'  class='   watupro-question-id-199205'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>3. <\/span>If E1 and E2 are two events, how do you represent the conditional probability given that E2 occurs given that E1 has occurred?<\/div><input type='hidden' name='question_id[]' id='qID_3' value='199205' \/><input type='hidden' id='answerType199205' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199205[]' id='answer-id-798789' class='answer   answerof-199205 ' value='798789'   \/><label for='answer-id-798789' id='answer-label-798789' class=' answer'><span>P(E1)\/P(E2)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199205[]' id='answer-id-798790' class='answer   answerof-199205 ' value='798790'   \/><label for='answer-id-798790' id='answer-label-798790' class=' answer'><span>P(E1+E2)\/P(E1)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199205[]' id='answer-id-798791' class='answer   answerof-199205 ' value='798791'   \/><label for='answer-id-798791' id='answer-label-798791' class=' answer'><span>P(E2)\/P(E1)<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199205[]' id='answer-id-798792' class='answer   answerof-199205 ' value='798792'   \/><label for='answer-id-798792' id='answer-label-798792' class=' answer'><span>P(E2)\/(P(E1+E2)<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-4' style=';'><div id='questionWrap-4'  class='   watupro-question-id-199206'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>4. <\/span>In which of the scenario you can use the regression to predict the values<\/div><input type='hidden' name='question_id[]' id='qID_4' value='199206' \/><input type='hidden' id='answerType199206' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199206[]' id='answer-id-798793' class='answer   answerof-199206 ' value='798793'   \/><label for='answer-id-798793' id='answer-label-798793' class=' answer'><span>Samsung can use it for mobile sales forecast<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199206[]' id='answer-id-798794' class='answer   answerof-199206 ' value='798794'   \/><label for='answer-id-798794' id='answer-label-798794' class=' answer'><span>Mobile companies can use it to forecast manufacturing defects<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199206[]' id='answer-id-798795' class='answer   answerof-199206 ' value='798795'   \/><label for='answer-id-798795' id='answer-label-798795' class=' answer'><span>Probability of the celebrity divorce<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199206[]' id='answer-id-798796' class='answer   answerof-199206 ' value='798796'   \/><label for='answer-id-798796' id='answer-label-798796' class=' answer'><span>Only 1 and 2<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199206[]' id='answer-id-798797' class='answer   answerof-199206 ' value='798797'   \/><label for='answer-id-798797' id='answer-label-798797' class=' answer'><span>All 1 ,2 and 3<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-5' style=';'><div id='questionWrap-5'  class='   watupro-question-id-199207'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>5. <\/span>You are working as a data science consultant for a gaming company. You have three member team and all other stake holders are from the company itself like project managers and project sponsored, data team etc. <br \/>\r<br>During the discussion project managed asked you that when can you tell me that the model you are using is robust enough, after which step you can consider answer for this question?<\/div><input type='hidden' name='question_id[]' id='qID_5' value='199207' \/><input type='hidden' id='answerType199207' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199207[]' id='answer-id-798798' class='answer   answerof-199207 ' value='798798'   \/><label for='answer-id-798798' id='answer-label-798798' class=' answer'><span>Data Preparation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199207[]' id='answer-id-798799' class='answer   answerof-199207 ' value='798799'   \/><label for='answer-id-798799' id='answer-label-798799' class=' answer'><span>Discovery<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199207[]' id='answer-id-798800' class='answer   answerof-199207 ' value='798800'   \/><label for='answer-id-798800' id='answer-label-798800' class=' answer'><span>Operationalize<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199207[]' id='answer-id-798801' class='answer   answerof-199207 ' value='798801'   \/><label for='answer-id-798801' id='answer-label-798801' class=' answer'><span>Model planning<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199207[]' id='answer-id-798802' class='answer   answerof-199207 ' value='798802'   \/><label for='answer-id-798802' id='answer-label-798802' class=' answer'><span>Model building<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-6' style=';'><div id='questionWrap-6'  class='   watupro-question-id-199208'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>6. <\/span>Logistic regression is a model used for prediction of the probability of occurrence of an event. It makes use of several variables that may be......<\/div><input type='hidden' name='question_id[]' id='qID_6' value='199208' \/><input type='hidden' id='answerType199208' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199208[]' id='answer-id-798803' class='answer   answerof-199208 ' value='798803'   \/><label for='answer-id-798803' id='answer-label-798803' class=' answer'><span>Numerical<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199208[]' id='answer-id-798804' class='answer   answerof-199208 ' value='798804'   \/><label for='answer-id-798804' id='answer-label-798804' class=' answer'><span>Categorical<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199208[]' id='answer-id-798805' class='answer   answerof-199208 ' value='798805'   \/><label for='answer-id-798805' id='answer-label-798805' class=' answer'><span>Both 1 and 2 are correct<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199208[]' id='answer-id-798806' class='answer   answerof-199208 ' value='798806'   \/><label for='answer-id-798806' id='answer-label-798806' class=' answer'><span>None of the 1 and 2 are correct<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-7' style=';'><div id='questionWrap-7'  class='   watupro-question-id-199209'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>7. <\/span>Select the statement which applies correctly to the Naive Bayes<\/div><input type='hidden' name='question_id[]' id='qID_7' value='199209' \/><input type='hidden' id='answerType199209' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199209[]' id='answer-id-798807' class='answer   answerof-199209 ' value='798807'   \/><label for='answer-id-798807' id='answer-label-798807' class=' answer'><span>Works with a small amount of data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199209[]' id='answer-id-798808' class='answer   answerof-199209 ' value='798808'   \/><label for='answer-id-798808' id='answer-label-798808' class=' answer'><span>Sensitive to how the input data is prepared<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199209[]' id='answer-id-798809' class='answer   answerof-199209 ' value='798809'   \/><label for='answer-id-798809' id='answer-label-798809' class=' answer'><span>Works with nominal values<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-8' style=';'><div id='questionWrap-8'  class='   watupro-question-id-199210'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>8. <\/span>The figure below shows a plot of the data of a data matrix M that is 1000 x 2. <br \/>\r<br><br><img decoding=\"async\" width=557 height=423 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image002-1.jpg\"><br><br \/>\r<br>Which line represents the first principal component?<\/div><input type='hidden' name='question_id[]' id='qID_8' value='199210' \/><input type='hidden' id='answerType199210' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199210[]' id='answer-id-798810' class='answer   answerof-199210 ' value='798810'   \/><label for='answer-id-798810' id='answer-label-798810' class=' answer'><span>yellow<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199210[]' id='answer-id-798811' class='answer   answerof-199210 ' value='798811'   \/><label for='answer-id-798811' id='answer-label-798811' class=' answer'><span>blue<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199210[]' id='answer-id-798812' class='answer   answerof-199210 ' value='798812'   \/><label for='answer-id-798812' id='answer-label-798812' class=' answer'><span>Neither<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-9' style=';'><div id='questionWrap-9'  class='   watupro-question-id-199211'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>9. <\/span>Refer to Exhibit <br \/>\r<br><br><img decoding=\"async\" width=498 height=482 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image003-1.jpg\"><br><br \/>\r<br>In the exhibit, the x-axis represents the derived probability of a borrower defaulting on a loan. Also in the exhibit, the pink represents borrowers that are known to have not defaulted on their loan, and the blue represents borrowers that are known to have defaulted on their loan. <br \/>\r<br>Which analytical method could produce the probabilities needed to build this exhibit?<\/div><input type='hidden' name='question_id[]' id='qID_9' value='199211' \/><input type='hidden' id='answerType199211' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199211[]' id='answer-id-798813' class='answer   answerof-199211 ' value='798813'   \/><label for='answer-id-798813' id='answer-label-798813' class=' answer'><span>Linear Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199211[]' id='answer-id-798814' class='answer   answerof-199211 ' value='798814'   \/><label for='answer-id-798814' id='answer-label-798814' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199211[]' id='answer-id-798815' class='answer   answerof-199211 ' value='798815'   \/><label for='answer-id-798815' id='answer-label-798815' class=' answer'><span>Discriminant Analysis<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199211[]' id='answer-id-798816' class='answer   answerof-199211 ' value='798816'   \/><label for='answer-id-798816' id='answer-label-798816' class=' answer'><span>Association Rules<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-10' style=';'><div id='questionWrap-10'  class='   watupro-question-id-199212'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>10. <\/span>You are working on a email spam filtering assignment, while working on this you find there is new word e.g. HadoopExam comes in email, and in your solutions you never come across this word before, hence probability of this words is coming in either email could be zero. <br \/>\r<br>So which of the following algorithm can help you to avoid zero probability?<\/div><input type='hidden' name='question_id[]' id='qID_10' value='199212' \/><input type='hidden' id='answerType199212' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199212[]' id='answer-id-798817' class='answer   answerof-199212 ' value='798817'   \/><label for='answer-id-798817' id='answer-label-798817' class=' answer'><span>Naive Bayes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199212[]' id='answer-id-798818' class='answer   answerof-199212 ' value='798818'   \/><label for='answer-id-798818' id='answer-label-798818' class=' answer'><span>Laplace Smoothing<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199212[]' id='answer-id-798819' class='answer   answerof-199212 ' value='798819'   \/><label for='answer-id-798819' id='answer-label-798819' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199212[]' id='answer-id-798820' class='answer   answerof-199212 ' value='798820'   \/><label for='answer-id-798820' id='answer-label-798820' class=' answer'><span>All of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-11' style=';'><div id='questionWrap-11'  class='   watupro-question-id-199213'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>11. <\/span>A bio-scientist is working on the analysis of the cancer cells. To identify whether the cell is cancerous or not, there has been hundreds of tests are done with small variations to say yes to the problem. Given the test result for a sample of healthy and cancerous cells, which of the following technique you will use to determine whether a cell is healthy?<\/div><input type='hidden' name='question_id[]' id='qID_11' value='199213' \/><input type='hidden' id='answerType199213' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199213[]' id='answer-id-798821' class='answer   answerof-199213 ' value='798821'   \/><label for='answer-id-798821' id='answer-label-798821' class=' answer'><span>Linear regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199213[]' id='answer-id-798822' class='answer   answerof-199213 ' value='798822'   \/><label for='answer-id-798822' id='answer-label-798822' class=' answer'><span>Collaborative filtering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199213[]' id='answer-id-798823' class='answer   answerof-199213 ' value='798823'   \/><label for='answer-id-798823' id='answer-label-798823' class=' answer'><span>Naive Bayes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199213[]' id='answer-id-798824' class='answer   answerof-199213 ' value='798824'   \/><label for='answer-id-798824' id='answer-label-798824' class=' answer'><span>Identification Test<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-12' style=';'><div id='questionWrap-12'  class='   watupro-question-id-199214'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>12. <\/span>Consider flipping a coin for which the probability of heads is p, where p is unknown, and our goa is to estimate p. The obvious approach is to count how many times the coin came up heads and divide by the total number of coin flips. If we flip the coin 1000 times and it comes up heads 367 times, it is very reasonable to estimate p as approximately 0.367. <br \/>\r<br>However, suppose we flip the coin only twice and we get heads both times. Is it reasonable to estimate p as 1.0? Intuitively, given that we only flipped the coin twice, it seems a bit rash to conclude that the coin will always come up heads, and____________is a way of avoiding such rash conclusions.<\/div><input type='hidden' name='question_id[]' id='qID_12' value='199214' \/><input type='hidden' id='answerType199214' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199214[]' id='answer-id-798825' class='answer   answerof-199214 ' value='798825'   \/><label for='answer-id-798825' id='answer-label-798825' class=' answer'><span>Naive Bayes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199214[]' id='answer-id-798826' class='answer   answerof-199214 ' value='798826'   \/><label for='answer-id-798826' id='answer-label-798826' class=' answer'><span>Laplace Smoothing<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199214[]' id='answer-id-798827' class='answer   answerof-199214 ' value='798827'   \/><label for='answer-id-798827' id='answer-label-798827' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199214[]' id='answer-id-798828' class='answer   answerof-199214 ' value='798828'   \/><label for='answer-id-798828' id='answer-label-798828' class=' answer'><span>Linear Regression<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-13' style=';'><div id='questionWrap-13'  class='   watupro-question-id-199215'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>13. <\/span>What is one modeling or descriptive statistical function in MADlib that is typically not provided in a standard relational database?<\/div><input type='hidden' name='question_id[]' id='qID_13' value='199215' \/><input type='hidden' id='answerType199215' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199215[]' id='answer-id-798829' class='answer   answerof-199215 ' value='798829'   \/><label for='answer-id-798829' id='answer-label-798829' class=' answer'><span>Expected value<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199215[]' id='answer-id-798830' class='answer   answerof-199215 ' value='798830'   \/><label for='answer-id-798830' id='answer-label-798830' class=' answer'><span>Variance<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199215[]' id='answer-id-798831' class='answer   answerof-199215 ' value='798831'   \/><label for='answer-id-798831' id='answer-label-798831' class=' answer'><span>Linear regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199215[]' id='answer-id-798832' class='answer   answerof-199215 ' value='798832'   \/><label for='answer-id-798832' id='answer-label-798832' class=' answer'><span>Quantiles<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-14' style=';'><div id='questionWrap-14'  class='   watupro-question-id-199216'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>14. <\/span>As a data scientist consultant at ABC Corp, you are working on a recommendation engine for the learning resources for end user. <br \/>\r<br>So Which recommender system technique benefits most from additional user preference data?<\/div><input type='hidden' name='question_id[]' id='qID_14' value='199216' \/><input type='hidden' id='answerType199216' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199216[]' id='answer-id-798833' class='answer   answerof-199216 ' value='798833'   \/><label for='answer-id-798833' id='answer-label-798833' class=' answer'><span>Naive Bayes classifier<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199216[]' id='answer-id-798834' class='answer   answerof-199216 ' value='798834'   \/><label for='answer-id-798834' id='answer-label-798834' class=' answer'><span>Item-based collaborative filtering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199216[]' id='answer-id-798835' class='answer   answerof-199216 ' value='798835'   \/><label for='answer-id-798835' id='answer-label-798835' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199216[]' id='answer-id-798836' class='answer   answerof-199216 ' value='798836'   \/><label for='answer-id-798836' id='answer-label-798836' class=' answer'><span>Content-based filtering<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-15' style=';'><div id='questionWrap-15'  class='   watupro-question-id-199217'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>15. <\/span>Which of the following technique can be used to the design of recommender systems?<\/div><input type='hidden' name='question_id[]' id='qID_15' value='199217' \/><input type='hidden' id='answerType199217' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199217[]' id='answer-id-798837' class='answer   answerof-199217 ' value='798837'   \/><label for='answer-id-798837' id='answer-label-798837' class=' answer'><span>Naive Bayes classifier<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199217[]' id='answer-id-798838' class='answer   answerof-199217 ' value='798838'   \/><label for='answer-id-798838' id='answer-label-798838' class=' answer'><span>Power iteration<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199217[]' id='answer-id-798839' class='answer   answerof-199217 ' value='798839'   \/><label for='answer-id-798839' id='answer-label-798839' class=' answer'><span>Collaborative filtering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199217[]' id='answer-id-798840' class='answer   answerof-199217 ' value='798840'   \/><label for='answer-id-798840' id='answer-label-798840' class=' answer'><span>1 and 3<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199217[]' id='answer-id-798841' class='answer   answerof-199217 ' value='798841'   \/><label for='answer-id-798841' id='answer-label-798841' class=' answer'><span>2 and 3<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-16' style=';'><div id='questionWrap-16'  class='   watupro-question-id-199218'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>16. <\/span>Regularization is a very important technique in machine learning to prevent over fitting. And Optimizing with a L1 regularization term is harder than with an L2 regularization term because<\/div><input type='hidden' name='question_id[]' id='qID_16' value='199218' \/><input type='hidden' id='answerType199218' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199218[]' id='answer-id-798842' class='answer   answerof-199218 ' value='798842'   \/><label for='answer-id-798842' id='answer-label-798842' class=' answer'><span>The penalty term is not differentiate<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199218[]' id='answer-id-798843' class='answer   answerof-199218 ' value='798843'   \/><label for='answer-id-798843' id='answer-label-798843' class=' answer'><span>The second derivative is not constant<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199218[]' id='answer-id-798844' class='answer   answerof-199218 ' value='798844'   \/><label for='answer-id-798844' id='answer-label-798844' class=' answer'><span>The objective function is not convex<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199218[]' id='answer-id-798845' class='answer   answerof-199218 ' value='798845'   \/><label for='answer-id-798845' id='answer-label-798845' class=' answer'><span>The constraints are quadratic<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-17' style=';'><div id='questionWrap-17'  class='   watupro-question-id-199219'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>17. <\/span>In which of the following scenario we can use naTve Bayes theorem for classification<\/div><input type='hidden' name='question_id[]' id='qID_17' value='199219' \/><input type='hidden' id='answerType199219' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199219[]' id='answer-id-798846' class='answer   answerof-199219 ' value='798846'   \/><label for='answer-id-798846' id='answer-label-798846' class=' answer'><span>Classify whether a given person is a male or a female based on the measured features. \r\nThe features include height, weight and foot size.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199219[]' id='answer-id-798847' class='answer   answerof-199219 ' value='798847'   \/><label for='answer-id-798847' id='answer-label-798847' class=' answer'><span>To classify whether an email is spam or not spam<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199219[]' id='answer-id-798848' class='answer   answerof-199219 ' value='798848'   \/><label for='answer-id-798848' id='answer-label-798848' class=' answer'><span>To identify whether a fruit is an orange or not based on features like diameter, color and shape<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-18' style=';'><div id='questionWrap-18'  class='   watupro-question-id-199220'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>18. <\/span>In unsupervised learning which statements correctly applies<\/div><input type='hidden' name='question_id[]' id='qID_18' value='199220' \/><input type='hidden' id='answerType199220' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199220[]' id='answer-id-798849' class='answer   answerof-199220 ' value='798849'   \/><label for='answer-id-798849' id='answer-label-798849' class=' answer'><span>It does not have a target variable<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199220[]' id='answer-id-798850' class='answer   answerof-199220 ' value='798850'   \/><label for='answer-id-798850' id='answer-label-798850' class=' answer'><span>Instead of telling the machine Predict Y for our data X, we're asking What can you tell me about X?<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199220[]' id='answer-id-798851' class='answer   answerof-199220 ' value='798851'   \/><label for='answer-id-798851' id='answer-label-798851' class=' answer'><span>telling the machine Predict Y for our data X<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-19' style=';'><div id='questionWrap-19'  class='   watupro-question-id-199221'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>19. <\/span>What is the best way to evaluate the quality of the model found by an unsupervised algorithm like k-means clustering, given metrics for the cost of the clustering (how well it fits the data) and its stability (how similar the clusters are across multiple runs over the same data)?<\/div><input type='hidden' name='question_id[]' id='qID_19' value='199221' \/><input type='hidden' id='answerType199221' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199221[]' id='answer-id-798852' class='answer   answerof-199221 ' value='798852'   \/><label for='answer-id-798852' id='answer-label-798852' class=' answer'><span>The lowest cost clustering subject to a stability constraint<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199221[]' id='answer-id-798853' class='answer   answerof-199221 ' value='798853'   \/><label for='answer-id-798853' id='answer-label-798853' class=' answer'><span>The lowest cost clustering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199221[]' id='answer-id-798854' class='answer   answerof-199221 ' value='798854'   \/><label for='answer-id-798854' id='answer-label-798854' class=' answer'><span>The most stable clustering subject to a minimal cost constraint<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199221[]' id='answer-id-798855' class='answer   answerof-199221 ' value='798855'   \/><label for='answer-id-798855' id='answer-label-798855' class=' answer'><span>The most stable clustering<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-20' style=';'><div id='questionWrap-20'  class='   watupro-question-id-199222'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>20. <\/span>Which of the following is not a correct application for the Classification?<\/div><input type='hidden' name='question_id[]' id='qID_20' value='199222' \/><input type='hidden' id='answerType199222' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199222[]' id='answer-id-798856' class='answer   answerof-199222 ' value='798856'   \/><label for='answer-id-798856' id='answer-label-798856' class=' answer'><span>credit scoring<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199222[]' id='answer-id-798857' class='answer   answerof-199222 ' value='798857'   \/><label for='answer-id-798857' id='answer-label-798857' class=' answer'><span>tumor detection<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199222[]' id='answer-id-798858' class='answer   answerof-199222 ' value='798858'   \/><label for='answer-id-798858' id='answer-label-798858' class=' answer'><span>image recognition<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199222[]' id='answer-id-798859' class='answer   answerof-199222 ' value='798859'   \/><label for='answer-id-798859' id='answer-label-798859' class=' answer'><span>drug discovery<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-21' style=';'><div id='questionWrap-21'  class='   watupro-question-id-199223'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>21. <\/span>Your customer provided you with 2. 000 unlabeled records three groups. <br \/>\r<br>What is the correct analytical method to use?<\/div><input type='hidden' name='question_id[]' id='qID_21' value='199223' \/><input type='hidden' id='answerType199223' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199223[]' id='answer-id-798860' class='answer   answerof-199223 ' value='798860'   \/><label for='answer-id-798860' id='answer-label-798860' class=' answer'><span>Semi Linear Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199223[]' id='answer-id-798861' class='answer   answerof-199223 ' value='798861'   \/><label for='answer-id-798861' id='answer-label-798861' class=' answer'><span>Logistic regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199223[]' id='answer-id-798862' class='answer   answerof-199223 ' value='798862'   \/><label for='answer-id-798862' id='answer-label-798862' class=' answer'><span>Naive Bayesian classification<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199223[]' id='answer-id-798863' class='answer   answerof-199223 ' value='798863'   \/><label for='answer-id-798863' id='answer-label-798863' class=' answer'><span>Linear regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199223[]' id='answer-id-798864' class='answer   answerof-199223 ' value='798864'   \/><label for='answer-id-798864' id='answer-label-798864' class=' answer'><span>K-means clustering<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-22' style=';'><div id='questionWrap-22'  class='   watupro-question-id-199224'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>22. <\/span>Which of the following steps you will be using in the discovery phase?<\/div><input type='hidden' name='question_id[]' id='qID_22' value='199224' \/><input type='hidden' id='answerType199224' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199224[]' id='answer-id-798865' class='answer   answerof-199224 ' value='798865'   \/><label for='answer-id-798865' id='answer-label-798865' class=' answer'><span>What all are the data sources for the project?<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199224[]' id='answer-id-798866' class='answer   answerof-199224 ' value='798866'   \/><label for='answer-id-798866' id='answer-label-798866' class=' answer'><span>Analyze the Raw data and its format and structure.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199224[]' id='answer-id-798867' class='answer   answerof-199224 ' value='798867'   \/><label for='answer-id-798867' id='answer-label-798867' class=' answer'><span>What all tools are required, in the project?<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199224[]' id='answer-id-798868' class='answer   answerof-199224 ' value='798868'   \/><label for='answer-id-798868' id='answer-label-798868' class=' answer'><span>What is the network capacity required<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199224[]' id='answer-id-798869' class='answer   answerof-199224 ' value='798869'   \/><label for='answer-id-798869' id='answer-label-798869' class=' answer'><span>What Unix server capacity required?<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-23' style=';'><div id='questionWrap-23'  class='   watupro-question-id-199225'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>23. <\/span>You are working on a problem where you have to predict whether the claim is done valid or not. And you find that most of the claims which are having spelling errors as well as corrections in the manually filled claim forms compare to the honest claims. <br \/>\r<br>Which of the following technique is suitable to find out whether the claim is valid or not?<\/div><input type='hidden' name='question_id[]' id='qID_23' value='199225' \/><input type='hidden' id='answerType199225' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199225[]' id='answer-id-798870' class='answer   answerof-199225 ' value='798870'   \/><label for='answer-id-798870' id='answer-label-798870' class=' answer'><span>Naive Bayes<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199225[]' id='answer-id-798871' class='answer   answerof-199225 ' value='798871'   \/><label for='answer-id-798871' id='answer-label-798871' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199225[]' id='answer-id-798872' class='answer   answerof-199225 ' value='798872'   \/><label for='answer-id-798872' id='answer-label-798872' class=' answer'><span>Random Decision Forests<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199225[]' id='answer-id-798873' class='answer   answerof-199225 ' value='798873'   \/><label for='answer-id-798873' id='answer-label-798873' class=' answer'><span>Any one of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-24' style=';'><div id='questionWrap-24'  class='   watupro-question-id-199226'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>24. <\/span>The method based on principal component analysis (PCA) evaluates the features according to<\/div><input type='hidden' name='question_id[]' id='qID_24' value='199226' \/><input type='hidden' id='answerType199226' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199226[]' id='answer-id-798874' class='answer   answerof-199226 ' value='798874'   \/><label for='answer-id-798874' id='answer-label-798874' class=' answer'><span>The projection of the largest eigenvector of the correlation matrix on the initial dimensions<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199226[]' id='answer-id-798875' class='answer   answerof-199226 ' value='798875'   \/><label for='answer-id-798875' id='answer-label-798875' class=' answer'><span>According to the magnitude of the components of the discriminate vector<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199226[]' id='answer-id-798876' class='answer   answerof-199226 ' value='798876'   \/><label for='answer-id-798876' id='answer-label-798876' class=' answer'><span>The projection of the smallest eigenvector of the correlation matrix on the initial dimensions<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199226[]' id='answer-id-798877' class='answer   answerof-199226 ' value='798877'   \/><label for='answer-id-798877' id='answer-label-798877' class=' answer'><span>None of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-25' style=';'><div id='questionWrap-25'  class='   watupro-question-id-199227'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>25. <\/span>Which is an example of supervised learning?<\/div><input type='hidden' name='question_id[]' id='qID_25' value='199227' \/><input type='hidden' id='answerType199227' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199227[]' id='answer-id-798878' class='answer   answerof-199227 ' value='798878'   \/><label for='answer-id-798878' id='answer-label-798878' class=' answer'><span>PCA<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199227[]' id='answer-id-798879' class='answer   answerof-199227 ' value='798879'   \/><label for='answer-id-798879' id='answer-label-798879' class=' answer'><span>k-means clustering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199227[]' id='answer-id-798880' class='answer   answerof-199227 ' value='798880'   \/><label for='answer-id-798880' id='answer-label-798880' class=' answer'><span>SVD<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199227[]' id='answer-id-798881' class='answer   answerof-199227 ' value='798881'   \/><label for='answer-id-798881' id='answer-label-798881' class=' answer'><span>EM<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199227[]' id='answer-id-798882' class='answer   answerof-199227 ' value='798882'   \/><label for='answer-id-798882' id='answer-label-798882' class=' answer'><span>SVM<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-26' style=';'><div id='questionWrap-26'  class='   watupro-question-id-199228'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>26. <\/span>You are designing a recommendation engine for a website where the ability to generate more personalized recommendations by analyzing information from the past activity of a specific user, or the history of other users deemed to be of similar taste to a given user. These resources are used as user profiling and helps the site recommend content on a user-by-user basis. The more a given user makes use of the system, the better the recommendations become, as the system gains data to improve its model of that user. <br \/>\r<br>What kind of this recommendation engine is?<\/div><input type='hidden' name='question_id[]' id='qID_26' value='199228' \/><input type='hidden' id='answerType199228' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199228[]' id='answer-id-798883' class='answer   answerof-199228 ' value='798883'   \/><label for='answer-id-798883' id='answer-label-798883' class=' answer'><span>Naive Bayes classifier<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199228[]' id='answer-id-798884' class='answer   answerof-199228 ' value='798884'   \/><label for='answer-id-798884' id='answer-label-798884' class=' answer'><span>Collaborative filtering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199228[]' id='answer-id-798885' class='answer   answerof-199228 ' value='798885'   \/><label for='answer-id-798885' id='answer-label-798885' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199228[]' id='answer-id-798886' class='answer   answerof-199228 ' value='798886'   \/><label for='answer-id-798886' id='answer-label-798886' class=' answer'><span>Content-based filtering<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-27' style=';'><div id='questionWrap-27'  class='   watupro-question-id-199229'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>27. <\/span>RMSE measures error of a predicted<\/div><input type='hidden' name='question_id[]' id='qID_27' value='199229' \/><input type='hidden' id='answerType199229' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199229[]' id='answer-id-798887' class='answer   answerof-199229 ' value='798887'   \/><label for='answer-id-798887' id='answer-label-798887' class=' answer'><span>Numerical Value<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199229[]' id='answer-id-798888' class='answer   answerof-199229 ' value='798888'   \/><label for='answer-id-798888' id='answer-label-798888' class=' answer'><span>Categorical values<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199229[]' id='answer-id-798889' class='answer   answerof-199229 ' value='798889'   \/><label for='answer-id-798889' id='answer-label-798889' class=' answer'><span>For booth Numerical and categorical values<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-28' style=';'><div id='questionWrap-28'  class='   watupro-question-id-199230'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>28. <\/span>Refer to exhibit <br \/>\r<br><br><img decoding=\"async\" width=284 height=143 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image004-1.jpg\"><br><br \/>\r<br>You are asked to write a report on how specific variables impact your client's sales using a data set provided to you by the client. The data includes 15 variables that the client views as directly related to sales, and you are restricted to these variables only. After a preliminary analysis of the data, the following findings were made: 1. Multicollinearity is not an issue among the variables 2. Only three variables-A, B, and C-have significant correlation with sales You build a linear regression model on the dependent variable of sales with the independent variables of A, B, and C. The results of the regression are seen in the exhibit. You cannot request additional data. <br \/>\r<br>What is a way that you could try to increase the R2 of the model without artificially inflating it?<\/div><input type='hidden' name='question_id[]' id='qID_28' value='199230' \/><input type='hidden' id='answerType199230' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199230[]' id='answer-id-798890' class='answer   answerof-199230 ' value='798890'   \/><label for='answer-id-798890' id='answer-label-798890' class=' answer'><span>Create clusters based on the data and use them as model inputs<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199230[]' id='answer-id-798891' class='answer   answerof-199230 ' value='798891'   \/><label for='answer-id-798891' id='answer-label-798891' class=' answer'><span>Force all 15 variables into the model as independent variables<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199230[]' id='answer-id-798892' class='answer   answerof-199230 ' value='798892'   \/><label for='answer-id-798892' id='answer-label-798892' class=' answer'><span>Create interaction variables based only on variables A, B, and C<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199230[]' id='answer-id-798893' class='answer   answerof-199230 ' value='798893'   \/><label for='answer-id-798893' id='answer-label-798893' class=' answer'><span>Break variables A, B, and C into their own univariate models<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-29' style=';'><div id='questionWrap-29'  class='   watupro-question-id-199231'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>29. <\/span>Which technique you would be using to solve the below problem statement? &quot;What is the probability that individual customer will not repay the loan amount?&quot;<\/div><input type='hidden' name='question_id[]' id='qID_29' value='199231' \/><input type='hidden' id='answerType199231' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199231[]' id='answer-id-798894' class='answer   answerof-199231 ' value='798894'   \/><label for='answer-id-798894' id='answer-label-798894' class=' answer'><span>Classification<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199231[]' id='answer-id-798895' class='answer   answerof-199231 ' value='798895'   \/><label for='answer-id-798895' id='answer-label-798895' class=' answer'><span>Clustering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199231[]' id='answer-id-798896' class='answer   answerof-199231 ' value='798896'   \/><label for='answer-id-798896' id='answer-label-798896' class=' answer'><span>Linear Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199231[]' id='answer-id-798897' class='answer   answerof-199231 ' value='798897'   \/><label for='answer-id-798897' id='answer-label-798897' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199231[]' id='answer-id-798898' class='answer   answerof-199231 ' value='798898'   \/><label for='answer-id-798898' id='answer-label-798898' class=' answer'><span>Hypothesis testing<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-30' style=';'><div id='questionWrap-30'  class='   watupro-question-id-199232'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>30. <\/span>Question-3: In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features (such as the words in a language), i.e., turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values modulo the number of features as indices directly, rather than looking the indices up in an associative array. <br \/>\r<br>So what is the primary reason of the hashing trick for building classifiers?<\/div><input type='hidden' name='question_id[]' id='qID_30' value='199232' \/><input type='hidden' id='answerType199232' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199232[]' id='answer-id-798899' class='answer   answerof-199232 ' value='798899'   \/><label for='answer-id-798899' id='answer-label-798899' class=' answer'><span>It creates the smaller models<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199232[]' id='answer-id-798900' class='answer   answerof-199232 ' value='798900'   \/><label for='answer-id-798900' id='answer-label-798900' class=' answer'><span>It requires the lesser memory to store the coefficients for the model<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199232[]' id='answer-id-798901' class='answer   answerof-199232 ' value='798901'   \/><label for='answer-id-798901' id='answer-label-798901' class=' answer'><span>It reduces the non-significant features e.g. punctuations<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199232[]' id='answer-id-798902' class='answer   answerof-199232 ' value='798902'   \/><label for='answer-id-798902' id='answer-label-798902' class=' answer'><span>Noisy features are removed<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-31' style=';'><div id='questionWrap-31'  class='   watupro-question-id-199233'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>31. <\/span>You have modeled the datasets with 5 independent variables called A, B, C, D and E having relationships which is not dependent each other, and also the variable A,B and C are continuous and variable D and E are discrete (mixed mode). <br \/>\r<br>Now you have to compute the expected value of the variable let say A, then which of the following computation you will prefer<\/div><input type='hidden' name='question_id[]' id='qID_31' value='199233' \/><input type='hidden' id='answerType199233' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199233[]' id='answer-id-798903' class='answer   answerof-199233 ' value='798903'   \/><label for='answer-id-798903' id='answer-label-798903' class=' answer'><span>Integration<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199233[]' id='answer-id-798904' class='answer   answerof-199233 ' value='798904'   \/><label for='answer-id-798904' id='answer-label-798904' class=' answer'><span>Differentiation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199233[]' id='answer-id-798905' class='answer   answerof-199233 ' value='798905'   \/><label for='answer-id-798905' id='answer-label-798905' class=' answer'><span>Transformation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199233[]' id='answer-id-798906' class='answer   answerof-199233 ' value='798906'   \/><label for='answer-id-798906' id='answer-label-798906' class=' answer'><span>Generalization<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-32' style=';'><div id='questionWrap-32'  class='   watupro-question-id-199234'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>32. <\/span>Clustering is a type of unsupervised learning with the following goals<\/div><input type='hidden' name='question_id[]' id='qID_32' value='199234' \/><input type='hidden' id='answerType199234' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199234[]' id='answer-id-798907' class='answer   answerof-199234 ' value='798907'   \/><label for='answer-id-798907' id='answer-label-798907' class=' answer'><span>Maximize a utility function<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199234[]' id='answer-id-798908' class='answer   answerof-199234 ' value='798908'   \/><label for='answer-id-798908' id='answer-label-798908' class=' answer'><span>Find similarities in the training data<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199234[]' id='answer-id-798909' class='answer   answerof-199234 ' value='798909'   \/><label for='answer-id-798909' id='answer-label-798909' class=' answer'><span>Not to maximize a utility function<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199234[]' id='answer-id-798910' class='answer   answerof-199234 ' value='798910'   \/><label for='answer-id-798910' id='answer-label-798910' class=' answer'><span>1 and 2<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199234[]' id='answer-id-798911' class='answer   answerof-199234 ' value='798911'   \/><label for='answer-id-798911' id='answer-label-798911' class=' answer'><span>2 and 3<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-33' style=';'><div id='questionWrap-33'  class='   watupro-question-id-199235'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>33. <\/span>Under which circumstance do you need to implement N-fold cross-validation after creating a regression model?<\/div><input type='hidden' name='question_id[]' id='qID_33' value='199235' \/><input type='hidden' id='answerType199235' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199235[]' id='answer-id-798912' class='answer   answerof-199235 ' value='798912'   \/><label for='answer-id-798912' id='answer-label-798912' class=' answer'><span>The data is unformatted.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199235[]' id='answer-id-798913' class='answer   answerof-199235 ' value='798913'   \/><label for='answer-id-798913' id='answer-label-798913' class=' answer'><span>There is not enough data to create a test set.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199235[]' id='answer-id-798914' class='answer   answerof-199235 ' value='798914'   \/><label for='answer-id-798914' id='answer-label-798914' class=' answer'><span>There are missing values in the data.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199235[]' id='answer-id-798915' class='answer   answerof-199235 ' value='798915'   \/><label for='answer-id-798915' id='answer-label-798915' class=' answer'><span>There are categorical variables in the model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-34' style=';'><div id='questionWrap-34'  class='   watupro-question-id-199236'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>34. <\/span>You have data of 10.000 people who make the purchasing from a specific grocery store. You also have their income detail in the data. You have created 5 clusters using this data. But in one of the cluster you see that only 30 people are falling as below 30, 2400, 2600, 2700, 2270 etc.&quot; <br \/>\r<br>What would you do in this case?<\/div><input type='hidden' name='question_id[]' id='qID_34' value='199236' \/><input type='hidden' id='answerType199236' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199236[]' id='answer-id-798916' class='answer   answerof-199236 ' value='798916'   \/><label for='answer-id-798916' id='answer-label-798916' class=' answer'><span>You will be increasing number of clusters.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199236[]' id='answer-id-798917' class='answer   answerof-199236 ' value='798917'   \/><label for='answer-id-798917' id='answer-label-798917' class=' answer'><span>You will be decreasing the number of clusters.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199236[]' id='answer-id-798918' class='answer   answerof-199236 ' value='798918'   \/><label for='answer-id-798918' id='answer-label-798918' class=' answer'><span>You will remove that 30 people from dataset<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199236[]' id='answer-id-798919' class='answer   answerof-199236 ' value='798919'   \/><label for='answer-id-798919' id='answer-label-798919' class=' answer'><span>You will be multiplying standard deviation with the 100<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-35' style=';'><div id='questionWrap-35'  class='   watupro-question-id-199237'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>35. <\/span>In which phase of the data analytics lifecycle do Data Scientists spend the most time in a project?<\/div><input type='hidden' name='question_id[]' id='qID_35' value='199237' \/><input type='hidden' id='answerType199237' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199237[]' id='answer-id-798920' class='answer   answerof-199237 ' value='798920'   \/><label for='answer-id-798920' id='answer-label-798920' class=' answer'><span>Discovery<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199237[]' id='answer-id-798921' class='answer   answerof-199237 ' value='798921'   \/><label for='answer-id-798921' id='answer-label-798921' class=' answer'><span>Data Preparation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199237[]' id='answer-id-798922' class='answer   answerof-199237 ' value='798922'   \/><label for='answer-id-798922' id='answer-label-798922' class=' answer'><span>Model Building<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199237[]' id='answer-id-798923' class='answer   answerof-199237 ' value='798923'   \/><label for='answer-id-798923' id='answer-label-798923' class=' answer'><span>Communicate Results<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-36' style=';'><div id='questionWrap-36'  class='   watupro-question-id-199238'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>36. <\/span>What is the probability that the total of two dice will be greater than 8, given that the first die is a 6?<\/div><input type='hidden' name='question_id[]' id='qID_36' value='199238' \/><input type='hidden' id='answerType199238' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199238[]' id='answer-id-798924' class='answer   answerof-199238 ' value='798924'   \/><label for='answer-id-798924' id='answer-label-798924' class=' answer'><span>1\/3<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199238[]' id='answer-id-798925' class='answer   answerof-199238 ' value='798925'   \/><label for='answer-id-798925' id='answer-label-798925' class=' answer'><span>2\/3<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199238[]' id='answer-id-798926' class='answer   answerof-199238 ' value='798926'   \/><label for='answer-id-798926' id='answer-label-798926' class=' answer'><span>1\/6<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199238[]' id='answer-id-798927' class='answer   answerof-199238 ' value='798927'   \/><label for='answer-id-798927' id='answer-label-798927' class=' answer'><span>2\/6<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-37' style=';'><div id='questionWrap-37'  class='   watupro-question-id-199239'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>37. <\/span>Which of the following is a correct example of the target variable in regression (supervised learning)?<\/div><input type='hidden' name='question_id[]' id='qID_37' value='199239' \/><input type='hidden' id='answerType199239' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199239[]' id='answer-id-798928' class='answer   answerof-199239 ' value='798928'   \/><label for='answer-id-798928' id='answer-label-798928' class=' answer'><span>Nominal values like true, false<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199239[]' id='answer-id-798929' class='answer   answerof-199239 ' value='798929'   \/><label for='answer-id-798929' id='answer-label-798929' class=' answer'><span>Reptile, fish, mammal, amphibian, plant, fungi<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199239[]' id='answer-id-798930' class='answer   answerof-199239 ' value='798930'   \/><label for='answer-id-798930' id='answer-label-798930' class=' answer'><span>Infinite number of numeric values, such as 0.100, 42.001, 1000.743..<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199239[]' id='answer-id-798931' class='answer   answerof-199239 ' value='798931'   \/><label for='answer-id-798931' id='answer-label-798931' class=' answer'><span>All of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-38' style=';'><div id='questionWrap-38'  class='   watupro-question-id-199240'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>38. <\/span>Which of the following true with regards to the K-Means clustering algorithm?<\/div><input type='hidden' name='question_id[]' id='qID_38' value='199240' \/><input type='hidden' id='answerType199240' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199240[]' id='answer-id-798932' class='answer   answerof-199240 ' value='798932'   \/><label for='answer-id-798932' id='answer-label-798932' class=' answer'><span>Labels are not pre-assigned to each objects in the cluster.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199240[]' id='answer-id-798933' class='answer   answerof-199240 ' value='798933'   \/><label for='answer-id-798933' id='answer-label-798933' class=' answer'><span>Labels are pre-assigned to each objects in the cluster.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199240[]' id='answer-id-798934' class='answer   answerof-199240 ' value='798934'   \/><label for='answer-id-798934' id='answer-label-798934' class=' answer'><span>It classify the data based on the labels.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199240[]' id='answer-id-798935' class='answer   answerof-199240 ' value='798935'   \/><label for='answer-id-798935' id='answer-label-798935' class=' answer'><span>It discovers the center of each cluster.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199240[]' id='answer-id-798936' class='answer   answerof-199240 ' value='798936'   \/><label for='answer-id-798936' id='answer-label-798936' class=' answer'><span>It find each objects fall in which particular cluster<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-39' style=';'><div id='questionWrap-39'  class='   watupro-question-id-199241'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>39. <\/span>A problem statement is given as below <br \/>\r<br>Hospital records show that of patients suffering from a certain disease, 75% die of it. <br \/>\r<br>What is the probability that of 6 randomly selected patients, 4 will recover? <br \/>\r<br>Which of the following model will you use to solve it?<\/div><input type='hidden' name='question_id[]' id='qID_39' value='199241' \/><input type='hidden' id='answerType199241' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199241[]' id='answer-id-798937' class='answer   answerof-199241 ' value='798937'   \/><label for='answer-id-798937' id='answer-label-798937' class=' answer'><span>Binomial<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199241[]' id='answer-id-798938' class='answer   answerof-199241 ' value='798938'   \/><label for='answer-id-798938' id='answer-label-798938' class=' answer'><span>Poisson<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199241[]' id='answer-id-798939' class='answer   answerof-199241 ' value='798939'   \/><label for='answer-id-798939' id='answer-label-798939' class=' answer'><span>Normal<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199241[]' id='answer-id-798940' class='answer   answerof-199241 ' value='798940'   \/><label for='answer-id-798940' id='answer-label-798940' class=' answer'><span>Any of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-40' style=';'><div id='questionWrap-40'  class='   watupro-question-id-199242'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>40. <\/span>A researcher is interested in how variables, such as GRE (Graduate Record Exam scores), GPA (grade point average) and prestige of the undergraduate institution, effect admission into graduate school. The response variable, admit\/don't admit, is a binary variable. <br \/>\r<br>Above is an example of<\/div><input type='hidden' name='question_id[]' id='qID_40' value='199242' \/><input type='hidden' id='answerType199242' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199242[]' id='answer-id-798941' class='answer   answerof-199242 ' value='798941'   \/><label for='answer-id-798941' id='answer-label-798941' class=' answer'><span>Linear Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199242[]' id='answer-id-798942' class='answer   answerof-199242 ' value='798942'   \/><label for='answer-id-798942' id='answer-label-798942' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199242[]' id='answer-id-798943' class='answer   answerof-199242 ' value='798943'   \/><label for='answer-id-798943' id='answer-label-798943' class=' answer'><span>Recommendation system<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199242[]' id='answer-id-798944' class='answer   answerof-199242 ' value='798944'   \/><label for='answer-id-798944' id='answer-label-798944' class=' answer'><span>Maximum likelihood estimation<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199242[]' id='answer-id-798945' class='answer   answerof-199242 ' value='798945'   \/><label for='answer-id-798945' id='answer-label-798945' class=' answer'><span>Hierarchical linear models<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-41' style=';'><div id='questionWrap-41'  class='   watupro-question-id-199243'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>41. <\/span>Which of the following statement true with regards to Linear Regression Model?<\/div><input type='hidden' name='question_id[]' id='qID_41' value='199243' \/><input type='hidden' id='answerType199243' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199243[]' id='answer-id-798946' class='answer   answerof-199243 ' value='798946'   \/><label for='answer-id-798946' id='answer-label-798946' class=' answer'><span>Ordinary Least Square can be used to estimates the parameters in linear model<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199243[]' id='answer-id-798947' class='answer   answerof-199243 ' value='798947'   \/><label for='answer-id-798947' id='answer-label-798947' class=' answer'><span>In Linear model, it tries to find multiple lines which can approximate the relationship between the outcome and input variables.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199243[]' id='answer-id-798948' class='answer   answerof-199243 ' value='798948'   \/><label for='answer-id-798948' id='answer-label-798948' class=' answer'><span>Ordinary Least Square is a sum of the individual distance between each point and the fitted line of regression model.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199243[]' id='answer-id-798949' class='answer   answerof-199243 ' value='798949'   \/><label for='answer-id-798949' id='answer-label-798949' class=' answer'><span>Ordinary Least Square is a sum of the squared individual distance between each point and the fitted line of regression model.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-42' style=';'><div id='questionWrap-42'  class='   watupro-question-id-199244'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>42. <\/span>Select the correct statement which applies to Supervised learning<\/div><input type='hidden' name='question_id[]' id='qID_42' value='199244' \/><input type='hidden' id='answerType199244' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199244[]' id='answer-id-798950' class='answer   answerof-199244 ' value='798950'   \/><label for='answer-id-798950' id='answer-label-798950' class=' answer'><span>We asks the machine to learn from our data when we specify a target variable.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199244[]' id='answer-id-798951' class='answer   answerof-199244 ' value='798951'   \/><label for='answer-id-798951' id='answer-label-798951' class=' answer'><span>Lesser machine's task to only divining some pattern from the input data to get the target variable<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199244[]' id='answer-id-798952' class='answer   answerof-199244 ' value='798952'   \/><label for='answer-id-798952' id='answer-label-798952' class=' answer'><span>Instead of telling the machine Predict Y for our data X, we're asking What can you tell me about X?<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-43' style=';'><div id='questionWrap-43'  class='   watupro-question-id-199245'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>43. <\/span>A data scientist wants to predict the probability of death from heart disease based on three risk factors: age, gender, and blood cholesterol level. <br \/>\r<br>What is the most appropriate method for this project?<\/div><input type='hidden' name='question_id[]' id='qID_43' value='199245' \/><input type='hidden' id='answerType199245' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199245[]' id='answer-id-798953' class='answer   answerof-199245 ' value='798953'   \/><label for='answer-id-798953' id='answer-label-798953' class=' answer'><span>Linear regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199245[]' id='answer-id-798954' class='answer   answerof-199245 ' value='798954'   \/><label for='answer-id-798954' id='answer-label-798954' class=' answer'><span>K-means clustering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199245[]' id='answer-id-798955' class='answer   answerof-199245 ' value='798955'   \/><label for='answer-id-798955' id='answer-label-798955' class=' answer'><span>Logistic regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199245[]' id='answer-id-798956' class='answer   answerof-199245 ' value='798956'   \/><label for='answer-id-798956' id='answer-label-798956' class=' answer'><span>Apriori algorithm<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-44' style=';'><div id='questionWrap-44'  class='   watupro-question-id-199246'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>44. <\/span>Question-34. Stories appear in the front page of Digg as they are &quot;voted up&quot; (rated positively) by the community. As the community becomes larger and more diverse, the promoted stories can better reflect the average interest of the community members. <br \/>\r<br>Which of the following technique is used to make such recommendation engine?<\/div><input type='hidden' name='question_id[]' id='qID_44' value='199246' \/><input type='hidden' id='answerType199246' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199246[]' id='answer-id-798957' class='answer   answerof-199246 ' value='798957'   \/><label for='answer-id-798957' id='answer-label-798957' class=' answer'><span>Naive Bayes classifier<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199246[]' id='answer-id-798958' class='answer   answerof-199246 ' value='798958'   \/><label for='answer-id-798958' id='answer-label-798958' class=' answer'><span>Collaborative filtering<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199246[]' id='answer-id-798959' class='answer   answerof-199246 ' value='798959'   \/><label for='answer-id-798959' id='answer-label-798959' class=' answer'><span>Logistic Regression<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199246[]' id='answer-id-798960' class='answer   answerof-199246 ' value='798960'   \/><label for='answer-id-798960' id='answer-label-798960' class=' answer'><span>Content-based filtering<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-45' style=';'><div id='questionWrap-45'  class='   watupro-question-id-199247'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>45. <\/span>What describes a true limitation of Logistic Regression method?<\/div><input type='hidden' name='question_id[]' id='qID_45' value='199247' \/><input type='hidden' id='answerType199247' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199247[]' id='answer-id-798961' class='answer   answerof-199247 ' value='798961'   \/><label for='answer-id-798961' id='answer-label-798961' class=' answer'><span>It does not handle redundant variables well.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199247[]' id='answer-id-798962' class='answer   answerof-199247 ' value='798962'   \/><label for='answer-id-798962' id='answer-label-798962' class=' answer'><span>It does not handle missing values well.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199247[]' id='answer-id-798963' class='answer   answerof-199247 ' value='798963'   \/><label for='answer-id-798963' id='answer-label-798963' class=' answer'><span>It does not handle correlated variables well.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199247[]' id='answer-id-798964' class='answer   answerof-199247 ' value='798964'   \/><label for='answer-id-798964' id='answer-label-798964' class=' answer'><span>It does not have explanatory values.<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-46' style=';'><div id='questionWrap-46'  class='   watupro-question-id-199248'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>46. <\/span>Select the choice where Regression algorithms are not best fit<\/div><input type='hidden' name='question_id[]' id='qID_46' value='199248' \/><input type='hidden' id='answerType199248' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199248[]' id='answer-id-798965' class='answer   answerof-199248 ' value='798965'   \/><label for='answer-id-798965' id='answer-label-798965' class=' answer'><span>When the dimension of the object given<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199248[]' id='answer-id-798966' class='answer   answerof-199248 ' value='798966'   \/><label for='answer-id-798966' id='answer-label-798966' class=' answer'><span>Weight of the person is given<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199248[]' id='answer-id-798967' class='answer   answerof-199248 ' value='798967'   \/><label for='answer-id-798967' id='answer-label-798967' class=' answer'><span>Temperature in the atmosphere<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199248[]' id='answer-id-798968' class='answer   answerof-199248 ' value='798968'   \/><label for='answer-id-798968' id='answer-label-798968' class=' answer'><span>Employee status<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-47' style=';'><div id='questionWrap-47'  class='   watupro-question-id-199249'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>47. <\/span>Refer to image below <br \/>\r<br><br><img decoding=\"async\" width=451 height=493 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image009-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_47' value='199249' \/><input type='hidden' id='answerType199249' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199249[]' id='answer-id-798969' class='answer   answerof-199249 ' value='798969'   \/><label for='answer-id-798969' id='answer-label-798969' class=' answer'><span>Option A<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199249[]' id='answer-id-798970' class='answer   answerof-199249 ' value='798970'   \/><label for='answer-id-798970' id='answer-label-798970' class=' answer'><span>Option B<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199249[]' id='answer-id-798971' class='answer   answerof-199249 ' value='798971'   \/><label for='answer-id-798971' id='answer-label-798971' class=' answer'><span>Option C<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199249[]' id='answer-id-798972' class='answer   answerof-199249 ' value='798972'   \/><label for='answer-id-798972' id='answer-label-798972' class=' answer'><span>Option D<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-48' style=';'><div id='questionWrap-48'  class='   watupro-question-id-199250'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>48. <\/span>A fruit may be considered to be an apple if it is red, round, and about 3&quot; in diameter. A naive Bayes classifier considers each of these features to contribute independently to the probability that this fruit is an apple, regardless of the<\/div><input type='hidden' name='question_id[]' id='qID_48' value='199250' \/><input type='hidden' id='answerType199250' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199250[]' id='answer-id-798973' class='answer   answerof-199250 ' value='798973'   \/><label for='answer-id-798973' id='answer-label-798973' class=' answer'><span>Presence of the other features.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199250[]' id='answer-id-798974' class='answer   answerof-199250 ' value='798974'   \/><label for='answer-id-798974' id='answer-label-798974' class=' answer'><span>Absence of the other features.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199250[]' id='answer-id-798975' class='answer   answerof-199250 ' value='798975'   \/><label for='answer-id-798975' id='answer-label-798975' class=' answer'><span>Presence or absence of the other features<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199250[]' id='answer-id-798976' class='answer   answerof-199250 ' value='798976'   \/><label for='answer-id-798976' id='answer-label-798976' class=' answer'><span>None of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-49' style=';'><div id='questionWrap-49'  class='   watupro-question-id-199251'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>49. <\/span>Suppose that the probability that a pedestrian will be tul by a car while crossing the toad at a pedestrian crossing without paying attention to the traffic light is lo be computed. Let H be a discrete random variable taking one value from (Hit. Not Hit). Let L be a discrete random variable taking one value from (Red. Yellow. Green). <br \/>\r<br>Realistically, H will be dependent on L That is, P(H = Hit) and P(H = Not Hit) will take different values depending on whether L is red, yellow or green. A person is. for example, far more likely to be hit by a car when trying to cross while Hie lights for cross traffic are green than if they are red In other words, for any given possible pair of values for Hand L. one must consider the joint probability distribution of H and L to find the probability* of that pair of events occurring together if Hie pedestrian ignores the state of the light Here is a table showing the conditional probabilities of being bit. defending on ibe stale of the lights (Note that the columns in this table must add up to 1 because the probability of being hit oi not hit is 1 regardless of the stale of the light.) <br \/>\r<br><br><img decoding=\"async\" width=452 height=294 src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/uploads\/2021\/11\/image011-1.jpg\"><br><\/div><input type='hidden' name='question_id[]' id='qID_49' value='199251' \/><input type='hidden' id='answerType199251' value='checkbox'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199251[]' id='answer-id-798977' class='answer   answerof-199251 ' value='798977'   \/><label for='answer-id-798977' id='answer-label-798977' class=' answer'><span>The marginal probability P(H=Hit) is the sum along the H=Hit row of this joint distribution table, as this is the probability of being hit when the lights are red OR yellow OR green.<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199251[]' id='answer-id-798978' class='answer   answerof-199251 ' value='798978'   \/><label for='answer-id-798978' id='answer-label-798978' class=' answer'><span>marginal probability that P(H=Not Hit) is the sum of the H=Not Hit row<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='checkbox' name='answer-199251[]' id='answer-id-798979' class='answer   answerof-199251 ' value='798979'   \/><label for='answer-id-798979' id='answer-label-798979' class=' answer'><span>marginal probability that P(H=Not Hit) is the sum of the H= Hit row<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div class='watu-question ' id='question-50' style=';'><div id='questionWrap-50'  class='   watupro-question-id-199252'>\n\t\t\t<div class='question-content'><div><span class='watupro_num'>50. <\/span>You recommend a movie with three stars but the user loves it (he'd rate it five stars). <br \/>\r<br>So which statement correctly applies?<\/div><input type='hidden' name='question_id[]' id='qID_50' value='199252' \/><input type='hidden' id='answerType199252' value='radio'><!-- end question-content--><\/div><div class='question-choices watupro-choices-columns '><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199252[]' id='answer-id-798980' class='answer   answerof-199252 ' value='798980'   \/><label for='answer-id-798980' id='answer-label-798980' class=' answer'><span>In both cases, the contribution to the RMSE is the same<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199252[]' id='answer-id-798981' class='answer   answerof-199252 ' value='798981'   \/><label for='answer-id-798981' id='answer-label-798981' class=' answer'><span>In both cases, the contribution to the RMSE is the different<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199252[]' id='answer-id-798982' class='answer   answerof-199252 ' value='798982'   \/><label for='answer-id-798982' id='answer-label-798982' class=' answer'><span>In both cases, the contribution to the RMSE, could varies<\/span><\/label><\/div><div class='watupro-question-choice  ' dir='auto' ><input type='radio' name='answer-199252[]' id='answer-id-798983' class='answer   answerof-199252 ' value='798983'   \/><label for='answer-id-798983' id='answer-label-798983' class=' answer'><span>None of the above<\/span><\/label><\/div><!-- end question-choices--><\/div><!-- end questionWrap--><\/div><\/div><div style='display:none' id='question-51'>\n\t<div class='question-content'>\n\t\t<img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.dumpsbase.com\/freedumps\/wp-content\/plugins\/watupro\/img\/loading.gif\" width=\"16\" height=\"16\" alt=\"Loading...\" title=\"Loading...\" \/>&nbsp;Loading...\t<\/div>\n<\/div>\n\n<br \/>\n\t\n\t\t\t<div class=\"watupro_buttons flex \" id=\"watuPROButtons5865\" >\n\t\t  <div id=\"prev-question\" style=\"display:none;\"><input type=\"button\" value=\"&lt; 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