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SPSS IBMSPSSMBPDM Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| IBM SPSS Modeler Environment | - Interface and stream design - Data flow and node usage |
| Model Evaluation and Validation | - Model comparison and selection - Performance metrics |
| Modeling Techniques | - Regression and clustering methods - Classification models |
| CRISP-DM Methodology | - Phases of CRISP-DM - Application in SPSS Modeler workflows |
| Model Deployment | - Scoring and deployment workflows - Operationalizing predictive models |
| Data Mining Fundamentals | - Core concepts of data mining - Business understanding and analytics objectives |
| Data Preparation | - Feature selection and preprocessing - Data cleaning and transformation |
SPSS IBM SPSS Modeler - Business Partner Data Mining Associate Sample Questions:
Question #1
How many phases are in the CRISP-DM Process Methodology?
A. Six
B. Five
C. Seven
D. Four
Question #2
Which node can be used to impute (estimate) missing values?
A. Filler node
B. Data Audit node
C. Reclassify node
D. Balance node
Question #3
Which of the following types of nodes will have data flowing both in and out, when used in a stream?
A. Sources
B. Graphs
C. Record Ops
D. Export
Solutions:
| Question #1 Correct Answer: A | Question #2 Correct Answer: B | Question #3 Correct Answer: C |
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