Gini Index, Information Gain, And Entropy

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Gini index, Information Gain, and Entropy are 3 commonly used measures in decision tree algorithms for feature selection. These measures are used to determine the best split of data into different subsets based on the values of a feature.

Gini index is a measure of impurity that is used in classification problems. It measures the probability of misclassifying a randomly chosen item in a dataset. A value of 0 indicates that all items in the dataset belong to the same class, while a value of 1 indicates that the items…