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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Preparation | 30% | - General operations in SPSS Modeler - Sampling, aggregating and cleaning data - Automated data preparation - Combining and restructuring data - Deriving and reclassifying variables |
| Topic 2: Business Understanding | 15% | |
| Topic 3: Evaluation and Deployment | 15% | - Interpreting and exporting results - Model assessment |
| Topic 4: Data Understanding | 20% | |
| Topic 5: Modeling | 20% | - CRISP-DM methodology - Applying data mining techniques |
1. To correctly read the Excel@ file shown below,
which dialog box settings are appropriate?
A) B)

D)
A) Exhibit A
B) Exhibit C
C) Exhibit D
D) Exhibit B
2. Which node can be used to impute (estimate) missing values?
A) Data Audit node
B) Filler node
C) Reclassify node
D) Balance node
3. True or false: the CRISP-DM Process Methodology is a linear process.
A) False
B) True
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A | Question # 3 Answer: A |
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