Identificare facilmente i gruppi e prevedere i risultati

IBM SPSS Decision Trees consente di identificare al meglio i gruppi, di rilevare le relazioni e prevedere gli eventi futuri.

Questo modulo integra strutture ad albero decisionale e di classificazione visuale. Queste strutture consentono di presentare risultati categorici in modo intuitivo, semplificando la spiegazione delle analisi categoriche a un pubblico non tecnico.

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Choose from four established tree-growing algorithms and discover hidden relationships in your data.

Diagram.
IBM SPSS Decision Trees diagrams,
tables and graphs are easy to interpret.
Use the highly visual trees to discover
relationships that are currently hidden in
your data. Use tree model results to score
cases directly in IBM SPSS Statistics.
IBM SPSS Decision Trees provides specialized tree-building techniques for classification – entirely within the IBM SPSS Statistics environment. It includes four established tree-growing algorithms:

With four algorithms, you have the ability to try different types of tree-growing algorithms and find the one that best fits your data.

Because you create classification trees directly within IBM SPSS Statistics, you can conveniently use the results to segment and group cases directly within the data. Additionally, you can generate selection or classification/prediction rules in the form of IBM SPSS Statistics syntax, SQL statements or simple text (through syntax).

You can display these rules in the Viewer and save them to an external file for later use to make predictions about individual and new cases. If you'd like to use your results to score other data files, you can write information from the tree model directly to your data or create XML models.

To enhance the power of IBM SPSS Decision Trees, we recommend using it with IBM SPSS Statistics Base.

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