Package | Description |
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org.apache.ignite.ml.tree.randomforest |
Contains random forest implementation classes.
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org.apache.ignite.ml.tree.randomforest.data.impurity |
Contains implementation of impurity computers based on histograms.
|
Class and Description |
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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.
|
GridGain In-Memory Computing Platform : ver. 8.9.9 Release Date : July 23 2024