Package  Description 

org.apache.ignite.ml.tree.randomforest 
Contains random forest implementation classes.

org.apache.ignite.ml.tree.randomforest.data.impurity 
Contains implementation of impurity computers based on histograms.

Class and Description 

GiniHistogram
Class contains implementation of splitting point finding algorithm based on Gini metric (see
https://en.wikipedia.org/wiki/Gini_coefficient) and represents a set of histograms in according to this metric.

ImpurityComputer
Interface represents an object that can compute best splitting point using features histograms.

ImpurityHistogramsComputer
Class containing logic of aggregation impurity statistics within learning dataset.

MSEHistogram
Class contains implementation of splitting point finding algorithm based on MSE metric (see
https://en.wikipedia.org/wiki/Mean_squared_error) and represents a set of histograms in according to this metric.

Class and Description 

GiniHistogram
Class contains implementation of splitting point finding algorithm based on Gini metric (see
https://en.wikipedia.org/wiki/Gini_coefficient) and represents a set of histograms in according to this metric.

ImpurityComputer
Interface represents an object that can compute best splitting point using features histograms.

ImpurityHistogram
Helper class for ImpurityHistograms.

ImpurityHistogramsComputer
Class containing logic of aggregation impurity statistics within learning dataset.

ImpurityHistogramsComputer.NodeImpurityHistograms
Class represents per feature statistics for impurity computing.

MSEHistogram
Class contains implementation of splitting point finding algorithm based on MSE metric (see
https://en.wikipedia.org/wiki/Mean_squared_error) and represents a set of histograms in according to this metric.

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