Question

Information gain in feature selection in weka how rank is given

Answer 1

Information Gain: The information gain is based on the decrease in entropy after a data-set is split on an attribute. Constructing a decision tree is all about finding attribute that returns the highest information gain (i.e., the most homogeneous branches).

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Answer 2

Answer:

☑ Information Gain. Information Gain (IG) is an entropy-based feature evaluation method, widely used in the field of machine learning. As Information Gain is used in feature selection, it is defined as the amount of information provided by the feature items for the text category.