It uses the flipTrees package, which uses the rpart package.
Apr 30, 1. Holdout some instances from training data. 2. Calculate misclassification for each of holdout set using the decision tree created. 3. Pruning is done if parent node has errors lesser than child node. After the full grown tree, we make trees out of it by pruning at different levels such that we have tree rolled up to the level of root node stumpcutting.bar: Shaily Jain. Oct 08, The decision trees need to be carefully tuned to make the most out of them. Too deep trees are likely to result in overfitting.
Scikit-learn provides several hyperparameters to control the growth of a tree. We will see how these hyperparameters achieve using the plot_tree function of the tree Estimated Reading Time: 4 mins.