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| Section | Objectives |
|---|---|
| Topic 1: SPSS Modeler Fundamentals | - Streams, nodes, and palettes - SPSS Modeler interface and navigation |
| Topic 2: Data Understanding and Preparation | - Data cleansing and transformation - Data exploration and visualization - Data import and data sources |
| Topic 3: Modeling and Analysis | - Model evaluation and deployment - Predictive modeling techniques |
| Topic 4: SPSS Modeler Solutions and Applications | - Business analytics use cases - Applying analytics methodologies |
1. Assume you have two data files: a personnel file with information about employees and a second file with information about performance categories. You will use IBM SPSS Modeler to merge the files together using performance category as the key. However, there are inconsistencies in the category keys used in both the personnel file and the performance file. In order to merge the files together without losing information from either the personnel file or the performance category file, you would use:
A) An anti-join.
B) An inner join.
C) A partial outer join.
D) A full outer join.
2. Summary statistics, such as mean, minimum, maximum, and standard deviation, are available in which of the following nodes? (Choose two.)
A) Table node
B) Statistics node
C) Sample node
D) Data Audit node
3. True or false: business objectives are the origin & every data mining solution.
A) True
B) False
4. In the Logistic node, can a Multinominal Mode/ option be used when the target is a flag field?
A) Yes
B) No
5. Which Model nodes can have a categorical target field? (Choose three.)
A) Neural Net node
B) Discriminant node
C) Linear node
D) C&R Tree node
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: B,D | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: A,B,D |
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