Easily identify groups and predict outcomes

IBM® SPSS® Decision Trees helps you better identify groups, discover relationships between them and predict future events. This module features highly visual classification and decision trees that enable you to present categorical results in an intuitive manner, so you can more clearly explain categorical analysis to non-technical audiences. It includes four tree-growing algorithms, giving you the ability to try different types and find the one that best fits your data.

The module provides specialized tree-building techniques for classification within the IBM SPSS Statistics environment. The four tree-growing algorithms include:

Opening dialog box

Use the decision tree dialog box to select the dependent and independent variables to be measured and choose a tree growing method.

Opening dialog box

CHAID method

The tree diagram is a graphic representation of the tree model. This tree diagram shows that, using the CHAID method, income level is the best predictor of credit rating.

CHAID method

Risk and classification tables

The risk and classification tables can provide a quick evaluation of how well a model used to classify customers by credit rating works.

Risk and classification tables

Tree-based classification model

The Decision Tree procedure creates a tree-based classification model. It classifies cases into groups or predicts values of a dependent (target) variable based on values of independent (predictor) variables.

Tree-based classification model

SPSS Decision Trees Screenshots

SPSS Decision Trees resources

Buy SPSS Decision Trees

Easily identify groups and predict outcomes

IBM Software Subscription and Support is included in the product price for the first year.

Download software online after purchase - no shipping costs.

More

Business analytics

Not in Suomi?

Me voimme auttaa