5.12. TA - R Predictive

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5.12. TA - R Predictive


All predictive Analytics actions have the same basic structure:

Set Target Variables (dependent variable)

Select Predictors variables (independent variables)

Set options


This information can be set manually by selecting variables, or by using an automated process.




Each node is explained in details in the following section. As the entire matrix will be sent to the R engine, it is a good idea to make a preselection of the relevant variables if you have many thousands of dimensions.


This section contains the following sub-sections:


5.12.1. Multivariate Outlier Detection (R action)

5.12.2. CART – Step 1 - Create one “deep” tree (R action)

5.12.3. CART – Step 2- Prune a “deep” tree (R action)

5.12.4. Neural Network & MultiNomial Logistic Prediction (R action)

5.12.5. Support Vector Machine (R action)

5.12.6. Naïve Bayes (R action)

5.12.7. XGBoost (R action)
5.12.8. Time Series (R action)

5.12.9. GLM (R action)

5.12.10. CHAID (R action)

5.12.11. Cox Model (R action)

5.12.12. Interactive CART (R action)

5.12.13. C50 (R action)