do you have description for parameters for decision-tree
https://github.com/neoml-lib/neoml/blob/master/NeoML/docs/en/API/ClassificationAndRegression/README.md#decision-tree
for example what parameters to set for unbalanced data?
what split you use
criterion{“gini”, “entropy”, “log_loss”}, default=”gini”
The function to measure the quality of a split. Supported criteria are “gini” for the Gini impurity and “log_loss” and “entropy” both for the Shannon information gain,
for example
https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html
do you have description for parameters for decision-tree
https://github.com/neoml-lib/neoml/blob/master/NeoML/docs/en/API/ClassificationAndRegression/README.md#decision-tree
for example what parameters to set for unbalanced data?
what split you use
criterion{“gini”, “entropy”, “log_loss”}, default=”gini”
The function to measure the quality of a split. Supported criteria are “gini” for the Gini impurity and “log_loss” and “entropy” both for the Shannon information gain,
for example
https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html