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IBM C2020-010 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Model Building Techniques | - Association and sequence modeling - Classification and regression models - Clustering and segmentation methods |
| Topic 2: Model Evaluation and Deployment | - Model comparison and selection - Model validation and performance evaluation - Deployment of predictive models |
| Topic 3: SPSS Modeler Fundamentals | - Data stream and project structure - Data import and preparation basics - Introduction to IBM SPSS Modeler environment |
| Topic 4: Advanced SPSS Modeler Features | - Integration with IBM analytics ecosystem - Stream optimization and performance tuning - Automated modeling (Auto Classifier, Auto Numeric) |
| Topic 5: Data Preparation and Transformation | - Data transformation and feature engineering - Field derivation and manipulation techniques - Data cleaning and handling missing values |
IBM SPSS Modeler Professional v2 Sample Questions:
Which node is best suited for revealing relationships between continuous and categorical (nominal, ordinal) fields?
- A. Distribution node
- B. Means node
- C. Table node
- D. Statistics node
Correct Answer: B 🗳️
Which statement is correct regarding the Sample node dialog shown below?
- A. It will select approximately 60% of the records. That is, each record will have a 60% probability of being selected.
- B. It will always draw the same 60% of the records each time this Sample node is run.
- C. It will randomly select exactly 60% of all the records.
- D. It will select every 60th record from the data.
Correct Answer: A 🗳️
Which node allows you to choose from many different graph types (bar charts, pie charts, scatterplots, heatmaps, etc.) in one single node?
- A. Evaluation node
- B. Graphboard node
- C. Multiplot node
- D. Collection node
Correct Answer: B 🗳️
What are the options for defining outliers in the Data Audit node? (Choose two.)
- A. Standard deviations from the mean
- B. Inter quartile range
- C. Values that represent less than 1% of all values
- D. Eigen values greater than 1
Correct Answer: A,B 🗳️
Assume you have four fields, 4, A, C and D and you wish to find the sum of the values even if there are $null$ missing values in one or more fields. Which expression would accomplish this task?
- A. A+B+C+D
- B. Sum_n((ABCIJ))
- C. to_real(A) + to_real(B) + to_real(C) + to_real(D)
- D. sum_n([A, B, C, D])
Correct Answer: D 🗳️
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