How can I tune the parameters of a decision tree model?

How can I tune the parameters of a decision tree model?

To tune a decision tree model, you can adjust parameters like max_depth, min_samples_split, and min_samples_leaf.

What is the impact of max_depth on the model's performance?

Max_depth controls how deep the tree can grow. A deeper tree can capture more patterns but may lead to overfitting.

How do I know if my model is overfitting?

You can check for overfitting by comparing the training and validation accuracy. A large gap indicates overfitting.

What techniques can I use to prevent overfitting?

You can use techniques like pruning, setting a maximum depth, or using ensemble methods like Random Forest.