Optimization Criteria : Gini impurity or Entropy/Info gain
Max Depth - Build trees with max. d depth deep; d = Number of nodes from top
min_samples_split: The minimum number of samples required to split an internal node
min_samples_leaf: The minimum number of samples required to be at a leaf node
max_features: The number of features to consider when looking for the best split
min_impurity_decrease: A node will be split if this split induces a decrease of the impurity greater than or equal to this value
class_weight:Weights associated with classes in the form {class_label: weight}
Monday, July 22, 2019
Decision Tree Important Hyper parameters
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