What is feature selection in decision trees?

What is feature selection in decision trees?

Feature selection in decision trees involves choosing the most relevant features to improve model performance.

Why is feature selection important?

It's important because it reduces overfitting, improves accuracy, and decreases training time.

How do decision trees perform feature selection?

Decision trees use algorithms like Gini impurity or information gain to evaluate and select the best features.

Can you give an example of feature selection in a decision tree?

Sure! For instance, in a dataset predicting house prices, features like location and size may be selected over others like color.