Overfitting
An overfitting model fits the training data too well, but it fails to do this on the new data.
Explanation
Pruning is a method that can help us avoid overfitting. It helps in improving the performance of the tree by cutting the nodes or sub-nodes which are not significant. It removes the branches which have very low importance.
Examples
The green line represents an overfitted model and the black line represents a regularized model. While the green line best follows the training data, it is too dependent on that data and it is likely to have a higher error rate on new unseen data, compared to the black line.
Outgoing relations
- Overfitting is part of Decision Tree