Predictive Modeling for Continuous Targets Using IBM SPSS Modeler (V18)
Predictive Modeling for Continuous Targets Using IBM SPSS Modeler (V18) is an intermediate level course that provides an overview of how to use IBM SPSS Modeler to predict a target field that describes numeric values. Students will be exposed to rule induction models such as CHAID and C&R Tree. They will also be introduced to traditional statistical models such as Linear Regression. Machine learning models will also be presented. Business use case examples include: predicting the length of subscription (for newspapers, telecommunication, job length, and so forth) and predicting claim amount (insurance).
This intermediate course is for IBM SPSS Modeler Analysts who have completed the Introduction to IBM SPSS Modeler and Data Mining course who want to become familiar with the modeling techniques available in IBM SPSS Modeler to predict a continuous target.
You should have:
- Completed Introduction to IBM SPSS Modeler and Data Mining (V18)
- Experience using IBM SPSS Modeler, including familiarity with the IBM SPSS Modeler environment, creating streams, importing data (Var. File node), basic data preparation (Type node, Derive node, Select node), reporting (Table node, Data Audit node), and creation of models
- Finding the Best Predictive Mode Introduction to Predicting Continuous Targets
- Building Your Tree Interactively
- Building Your Tree Directly
- Using Traditional Statistical Models
- Using Machine Learning Models