Information Gain Calculator

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This node allows to calculate the information gain score for all features of a given dataset. The provided output is a table with all feature names in the dataset and an associated information gain score. An explanation of the information gain feature selection criterion can be found for example in “A Comparative Study on Feature Selection in Text Categorization”, Yiming Yang, Jan O. Pedersen, 1997.

The information gain measure is usually employed to select the best split in a tree node when building decision trees. This node allows to calculate the information gain values for a list of features and output it as a single list, so that the worth of a given features can be analyzed conveniently.


Class input
The column which contains the nominal class value

Input Ports

Classified data with nominal and/or numeric features and a nominal class value

Output Ports

A table which contains a row for each feature with an associated information gain value


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