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C2090-930 Dumps

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Exam Name

IBM SPSS Modeler Professional v3

Updated
2018-09-22
Q&A
60

About C2090-930 Exam

IBM Certified Specialist-SPSS Modeler Professional v3 certification requires to pass IBM C2090-930 exam. What is the best way to pass IBM C2090-930 exam and get this certification? Dumpsbase IBM Certified Specialist C2090-930 exam dumps can help you achieve the goal.

C2090-930 Exam Basic Information

IBM Certified Specialist C2090-930 exam basic information is below for you to learn the test well. You have 90 minutes to complete all of 60 questions in IBM Certified Specialist C2090-930 exam. The number of questions required to pass IBM C2090-930 exam is 40. IBM SPSS Modeler Professional v3 C2090-930 languages are English and Japanese. Dumpsbase IBM Certified Specialist C2090-930 exam dumps cover over 95% of real exam questions.

C2090-930 Exam Topics

There are 7 sections in real IBM Certified Specialist C2090-930 exam topics. Dumpsbase IBM Certified Specialist C2090-930 dumps questions contain all of 7 sections. 

Section 1 Business Understanding and Planning 10%
Section 2 Data Preparation 20%
Section 3 Data Understanding 15%
Section 4 Deployment 10%
Section 5 Evaluation and Analysis 15%
Section 6 Modeling 20%
Section 7 SPSS Modeler Professional Functionality 10%
The above IBM C2090-930 exam basic information and exam topics are collected by our experts from IBM official website. 

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Question No : 1

What is the primary purpose of the Partition node in a modeling effort?
A. Divide the data into training and testing data.
B. Increase the proportion of under-represented subgroups within the data.
C. Decrease the proportion of an over-represented subgroup within the data.
D. Allow for equal sampling across subgroups within the data.
Answer: C

Question No : 2

You have a large amount of data from which you want to build a model. Although many of the
records of data are complete, there are substantial amounts of records which contain missing data. The records containing incomplete information should be excluded from analysis.
Which node will exclude the undesired records?
A. Filler node
B. Filter node
C. Select node
D. Aggregate node
Answer: A

Question No : 3

You have two data sets. One data set contains customer name and age information along with a customer ID. The second data set contains the customer ID along with address information. There are no addresses which do not belong to a customer, there are customers which have no address, and there are customers which have multiple addresses.
Which type of join will display all customers who have no recorded address?
A. Inner join
B. Outer join
C. Partial outer join
D. Anti-join
Answer: B

Question No : 4

Which two statements are true about linear regression? (Choose two.)
A. The estimation method of coefficient is ordinary least squares.
B. Methods for variable entry and removal are Enter Stepwise, Forward, and Backward.
C. The calculation of the predictor importance is based on Regression Sum-of-Squares.
D. Adjusted R-Squared is not a measure for Goodness-of-Fit.
Answer: B,C

Question No : 5

You need to export data using IBM SPSS Modeler Professional.
Which two nodes should be used to accomplish this task? (Choose two.)
A. Database
B. Select
C. Flat File
D. Filter
Answer: A,C

Question No : 6

You have a data set with numeric fields (columns) that contain null values. You want to replace each of these null values with the value of zero.
Which node will you use to accomplish this task?
A. Type node
B. Filler node
C. Filter node
D. Binning node
Answer: A

Question No : 7

You want to calculate the difference between the minimum and maximum values of some of your data fields.
Which feature or mode of the Aggregate node would allow you to calculate this using a single node?
A. Aggregate expressions
B. Median mode
C. Default mode
D. Key field grouping
Answer: B

Question No : 8

You need to determine whether a variable should be removed in the stepwise variable selection methods in logistic regression.
Which two metrics are used to accomplish this task? (Choose two.)
A. Wald Statistic
B. KS-Statistic
C. Likelihood Ratio (LR) Statistic
D. Z-Statistic
Answer: A,C

Question No : 9

Referring to the exhibit,



from which node is the output generated and on which data does it show greater accuracy?
A. Statistics, 1_Training
B. Statistics, 2_Testing
C. Analysis, 1_Training
D. Analysis, 2_Testing
Answer: C

Question No : 10

You have optimized four models that do not meet your performance goals. You believe that by mergingthese models together you would achieve better performance.
Which node would allow you to accomplish this task?
A. Aggregate node
B. Reclassify node
C. Regression node
D. Ensemble node
Answer: B

Question No : 11

A client has a business goal of increasing units sold by 10 percent.
Which two data mining objectives would be consistent with their business goal? (Choose two.)
A. Create a profile of customers most likely to default on their account.
B. Create a profile of current high value customers' purchasing patterns.
C. Reduce marketing costs.
D. Determine which products should be grouped together on the shopping Web site.
Answer: B,D

Question No : 12

You have a data source which provides many fields needed for data scoring. Some of these fields are not needed after the scoring is complete for the rest of the stream to operate.
Which node should be used to remove these fields?
A. Filter node
B. Select node
C. Sample Node
D. Type node
Answer: C

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