| Interface | Description |
|---|---|
| Impurity |
:: Experimental ::
Trait for calculating information gain.
|
| Class | Description |
|---|---|
| Entropy |
:: Experimental ::
Class for calculating
entropy during
binary classification. |
| EntropyAggregator |
Class for updating views of a vector of sufficient statistics,
in order to compute impurity from a sample.
|
| EntropyCalculator |
Stores statistics for one (node, feature, bin) for calculating impurity.
|
| Gini |
:: Experimental ::
Class for calculating the
Gini impurity
during binary classification. |
| GiniAggregator |
Class for updating views of a vector of sufficient statistics,
in order to compute impurity from a sample.
|
| GiniCalculator |
Stores statistics for one (node, feature, bin) for calculating impurity.
|
| Impurities |
Factory for Impurity instances.
|
| ImpurityAggregator |
Interface for updating views of a vector of sufficient statistics,
in order to compute impurity from a sample.
|
| ImpurityCalculator |
Stores statistics for one (node, feature, bin) for calculating impurity.
|
| Variance |
:: Experimental ::
Class for calculating variance during regression
|
| VarianceAggregator |
Class for updating views of a vector of sufficient statistics,
in order to compute impurity from a sample.
|
| VarianceCalculator |
Stores statistics for one (node, feature, bin) for calculating impurity.
|