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IBM C2020-010 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Administration and Troubleshooting | 10% | - Process Engine logs and diagnostics - Performance tuning and monitoring |
| Data Preparation | 30% | - Data cleaning and transformation - Type node and data coercion - Merge, Append, and Field operations - Sampling, balancing, and dimensionality reduction |
| Business and Data Understanding | 20% | - Data sources and import using Source nodes - Data visualization and distribution analysis - CRISP-DM methodology and business objectives |
| Modeling | 25% | - SQL pushback and performance optimization - Supervised and unsupervised learning methods - Model types and Auto Modeling nodes |
| Evaluation and Deployment | 15% | - Export and score new data - Model evaluation and comparison - Monitoring deployed models |
IBM SPSS Modeler Professional v2 Sample Questions:
1. Which statement about the Filler dialog shown below is correct?
A) None of the statements is correct.
B) The missing values for both GE and INCOME will be replaced by zeroes.
C) Missing values for the field @RELD will be replaced.
D) No missing values will be replaced because neither field was specified in the Condition box for missing value replacement.
2. Which Model nodes can have a categorical target field? (Choose three.)
A) Linear node
B) Neural Net node
C) C&R Tree node
D) Discriminant node
3. In order to make Decision Tree models more general, avoid overfitting, and make the trees less complex, what would you need to change in the dialog below? (Choose two.)
A) Increase the pruning severity.
B) Decrease the pruning severity.
C) Decrease the Minimum records per child branch.
D) Increase the Minimum records per child branch.
4. What are the options for defining outliers in the Data Audit node? (Choose two.)
A) Values that represent less than 1% of all values
B) Eigen values greater than 1
C) Inter quartile range
D) Standard deviations from the mean
5. Some data mining models such as Neural Net and Support Vector Machine models do not provide equations or rules to help analysts determine how the models use the input fields for prediction. If you have a categorical target field and a continuous input field, which graphing technique could aid with interpretation?
A) Distribution node
B) Plot node
C) Evaluation node
D) Histogram node
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B,C,D | Question # 3 Answer: A,D | Question # 4 Answer: C,D | Question # 5 Answer: D |
