Question

what is information gain? where is it used? what makes sense?

Answer 1

Answer- Imformation gain is a method that is used to calculate the reduction in entropy or surprise from transforming a dataset in some way.

It is used in the construction of decision trees from a training dataset. The decision tree is constructed by evaluating the information gain for each variable, and selecting the variable that maximizes the information gain, which in turn minimizes the entropy. It is the one that best splits the dataset into groups for effective classification. Information gain is also used for feature selection. Feature selection is done by evaluating the gain of each variable in the context of the target variable.