Predictive Modeling for Continuous Targets Using IBM SPSS Modeler (v18) (0A0V7G)

 

Who should attend

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.

Prerequisites

• 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. • Introduction to IBM SPSS Modeler and Data Mining (v18)

Course Objectives

This course (formerly Predicting Continuous Targets Using IBM SPSS Modeler (v16)) 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).

Course Content

This course (formerly Predicting Continuous Targets Using IBM SPSS Modeler (v16)) 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).

Prices & Delivery methods

Classroom Training
Modality: C

Duration 1 day

Price
  • Eastern Europe: 790.— €

Currently there are no training dates scheduled for this course.