Does the optimal depth vary depending on the metric of interest?

Sep 8, 2023 ... ... max depth of a tree, we want to do the following: 1. Use the train data to learn a decision tree classifier. 2. Use our trained classifier ... Jul 11, 2017 ... After using the PROC HPSPLIT, a decision tree with at depth of 10 is returned. ... proc hpsplit data=x.hmeq seed=123 maxdepth=10 plots ... Nov 25, 2017 ... The thumb rule is to have a max depth of roughly log (base 2) of number of attributes. So if you indeed have tree(s) with depth 17000 (!!!), you are getting ... compare the decision tree classification and the random forest classification in terms of overfitting and underfitting, ... max depth') plt.ylabel('accuracy') plt ... Jan 18, 2023 ... ... tree.DecisionTreeClassifier as you search for an optimal max depth parameter. Vary the depth of your decision tree using max depth = 1,2,. . . , ... Including number of levels (maximal depth) and number of nodes in a tree. ... Training a decision tree and training a random forest of decision trees. Dec 20, 2021 ... (C) Maximum depth (D) Gini impurity. Question 5: Suppose in a classification problem, you are using a decision tree and you use the Gini ... Dec 3, 2019 ... When you reach the maximum tree depth and still have not got a U-turn, you will get a warning. It does not effect the correctness of the sampler ... Mar 20, 2019 ... Interpreting and Visualizing Black-Box Classification Models with Surrogate Decision Tree ... value for Max Depth for the decision tree. Being ... Oct 30, 2024 ... Max Depth: The maximum depth of the tree. Limits growth to avoid overfitting. Min Samples Split: The minimum number of samples required to ...