IBM SPSS Modeler Professional v3 Exam Dumps

C2090-930 Exam Format | Course Contents | Course Outline | Exam Syllabus | Exam Objectives

Exam Name : IBM Certified Specialist - SPSS Modeler Professional v3

Exam Code : C2090-930

Number of questions: 60

Number of questions to pass: 40

Time allowed: 90 mins

Status: Live



SPSS Modeler Professional Functionality 10%

Identify the purpose of each palette

Describe the use of SuperNodes

Describe the advantages of SPSS Modeler scripting



Business Understanding and Planning 10%

Describe the CRISP-DM process

Describe how to map business objectives to data mining goals



Data Understanding 15%

Describe appropriate nodes for summary statistics, distributions, and visualizations (for example, graph nodes, output nodes)

Describe data quality issues (for example, outliers and missing data)



Data Preparation 20%

Describe methods for data transformation (for example, Derive node, Auto Data Prep node, Data Audit node and Filler node)

Describe how to integrate data (for example, Merge node and Append node)

Describe sampling, partitioning, and balancing data (for example, Sample node, Balance node and Partition node)

Describe methods for refining data (for example, Select node, Filter node and Aggregate node)



Modeling 20%

Describe classification models (including GLM and regression)

Describe segmentation models

Describe association models

Describe auto modeling nodes

Demonstrate how to combine models using the Ensemble node



Evaluation and Analysis 15%

Demonstrate how to interpret SPSS Modeler results (for example, using Evaluation node, Analysis node, and data visualizations)

Describe how to use model nugget interfaces



Deployment 10%

Describe how to use Export nodes (tools for exporting data)

Identify how to score new data using models

Identify SPSS Modeler reporting methods

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C2090-930 PDF Sample Questions

C2090-930 Sample Questions

IBM
C2090-930
IBM SPSS Modeler Professional v3
https://killexams.com/pass4sure/exam-detail/C2090-930
QUESTION: 52
What is an accurate description of the purpose of data segmentation?
A. Separate an individual data field into a predefined number of equal-sized groups
according to the field values.
B. Assemble similar data across data sets by using a primary key.
C. Separate a data set into two equal partitions in preparation for continued
analysis.
D. Group data using one or more fields to produce subsets with similar attributes.
Answer: D
QUESTION: 53
You have duplicate records that must be removed from a data set in IBM SPSS
Modeler Professional. The appropriate node to perform this action would be found
in which palette tab?
A. Sources
B. Record Ops
C. Field Ops
D. Export
Answer: B
Reference:
http://www-
01.ibm.com/support/knowledgecenter/SS3RA7_17.0.0/clementine/record_ops_nod
es.html
QUESTION: 54
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: C
QUESTION: 55
Exhibit
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: B
QUESTION: 56
Your data contains 5,000 sales transactions across twelve regions. Which node
would reduce your data, showing the average sales amount for each region?
A. Aggregate node
B. Select node
C. Filter node
D. Derive node
Answer: D
QUESTION: 57
You are provided two data sources which both contain event IDs and the date/time
that the events occurred. Which node will merge these two data sources?
A. Append node
B. Filter node
C. Aggregate node
D. Sort node
Answer: A
QUESTION: 58
What are two purposes of model nuggets? (Choose two.)
A. Scoring data to generate predictions
B. Enabling further analysis of the model properties
C. Merging of two or more data sets
D. Reducing the number of columns in a data set
Answer: B, D
QUESTION: 59
Exhibit
Referring to the exhibit, respectively, which field is the predicted value and what is
the confidence that you have in the prediction?
A. $XS-Credit rating; $XSC-Credit rating
B. Credit rating; $XSC-Credit rating
C. $XSC-Credit rating; $XS-Credit rating
D. Credit rating; $XS-Credit rating
Answer: D
QUESTION: 60
Which modeling node is supported in both Auto Classifier and Auto Numeric
modeling nodes?
A. Decision List
B. Bayesian Network
C. Discriminant
D. Neural Net
Answer: C
Reference:
ftp://ftp.software.ibm.com/software/analytics/spss/documentation/modeler/14.2/en/
Modeling Nodes.pdf
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