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IBM C2020-010 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Advanced SPSS Modeler Features | - Stream optimization and performance tuning - Integration with IBM analytics ecosystem - Automated modeling (Auto Classifier, Auto Numeric) |
| Topic 2: Model Evaluation and Deployment | - Model validation and performance evaluation - Deployment of predictive models - Model comparison and selection |
| Topic 3: Model Building Techniques | - Classification and regression models - Association and sequence modeling - Clustering and segmentation methods |
| Topic 4: SPSS Modeler Fundamentals | - Data import and preparation basics - Data stream and project structure - Introduction to IBM SPSS Modeler environment |
| Topic 5: Data Preparation and Transformation | - Data cleaning and handling missing values - Field derivation and manipulation techniques - Data transformation and feature engineering |
IBM SPSS Modeler Professional v2 Sample Questions:
1. Suppose you wanted to select only the records with complete data on all the fields for analysis and need to generate a Select node to perform that operation. Which other node should you use to generate the Select node?
A) Derive node
B) Data Audit node
C) Filter node
D) Filler node
2. Which statement accurately describes the function of the Coerce data check setting on the Type node?
A) Checks all fields for values outside the specified range and reports unspecified values.
B) Checks fully instantiated fields for values outside the specified range and reports unspecified values.
C) None of the above is accurate.
D) Checks fully instantiated fields for values outside the specified range and converts unspecified values to legal values.
3. Which Model nodes can have a categorical target field? (Choose three.)
A) Linear node
B) Neural Net node
C) Discriminant node
D) C&R Tree node
4. Using the Linear node, what are the advantages of creating a standard model without boosting or bagging? (Choose two.)
A) Easter to score
B) Higher accuracy
C) Easier interpretation
D) None of the above
5. What are the advantages of pruning Decision Tree models? (Choose three.)
A) Pruning can increase the accuracy of the tree.
B) Pruning can help simplify the tree.
C) Pruning can improve the generalization of the tree.
D) Pruning can make the tree easier to interpret.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: B,C,D | Question # 4 Answer: A,C | Question # 5 Answer: B,C,D |
