Post-pruning Decision Tree with Cost Complexity Parameter ccp_alpha
Now put the printed best_model here below and run:
Day: March 8, 2024
Pre-pruning Decision Tree – GridSearch for Hyperparameter tuning
Grid search is a tuning technique that attempts to compute the optimum values of hyperparameters. It is an exhaustive search that is performed on the specific parameter values of a model. The parameters of the estimator/model used to apply these methods are optimized by cross-validated grid-search over a parameter grid.
Pre-pruning Decision Tree – depth restricted
In general, the deeper you allow your tree to grow, the more complex your model will become because you will have more splits and it captures more information about the data and this is one of the root causes of overfitting. We can limit the tree with max_depth of tree: