Interface RegressorImpurity
- All Superinterfaces:
com.oracle.labs.mlrg.olcut.config.Configurable
,com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
- All Known Implementing Classes:
MeanAbsoluteError
,MeanSquaredError
public interface RegressorImpurity
extends com.oracle.labs.mlrg.olcut.config.Configurable, com.oracle.labs.mlrg.olcut.provenance.Provenancable<com.oracle.labs.mlrg.olcut.provenance.ConfiguredObjectProvenance>
Calculates a tree impurity score based on the regression targets.
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Nested Class Summary
Modifier and TypeInterfaceDescriptionstatic class
Tuple class for the impurity and summed weight. -
Method Summary
Modifier and TypeMethodDescriptiondouble
impurity
(float[] targets, float[] weights) Calculates the impurity based on the supplied weights and targets.default double
impurity
(int[] indices, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices array.default double
impurity
(int[] indices, int indicesLength, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices array.default double
Calculates the weighted impurity of the targets specified in all the indices arrays.default double
impurity
(IntArrayContainer indices, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices container.impurityTuple
(int[] indices, int indicesLength, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices array.impurityTuple
(List<int[]> indices, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in all the indices arrays.Methods inherited from interface com.oracle.labs.mlrg.olcut.config.Configurable
postConfig
Methods inherited from interface com.oracle.labs.mlrg.olcut.provenance.Provenancable
getProvenance
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Method Details
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impurity
double impurity(float[] targets, float[] weights) Calculates the impurity based on the supplied weights and targets.- Parameters:
targets
- The targets.weights
- The weights.- Returns:
- The impurity.
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impurityTuple
RegressorImpurity.ImpurityTuple impurityTuple(int[] indices, int indicesLength, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices array.- Parameters:
indices
- The indices in the targets and weights arrays.indicesLength
- The number of values to use in indices.targets
- The regression targets.weights
- The example weights.- Returns:
- A tuple containing the impurity and the used weight sum.
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impurityTuple
RegressorImpurity.ImpurityTuple impurityTuple(List<int[]> indices, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in all the indices arrays.- Parameters:
indices
- The indices in the targets and weights arrays.targets
- The regression targets.weights
- The example weights.- Returns:
- A tuple containing the impurity and the used weight sum.
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impurity
default double impurity(int[] indices, int indicesLength, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices array.- Parameters:
indices
- The indices in the targets and weights arrays.indicesLength
- The number of values to use in indices.targets
- The regression targets.weights
- The example weights.- Returns:
- The weighted impurity.
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impurity
Calculates the weighted impurity of the targets specified in all the indices arrays.- Parameters:
indices
- The indices in the targets and weights arrays.targets
- The regression targets.weights
- The example weights.- Returns:
- The weighted impurity.
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impurity
default double impurity(int[] indices, float[] targets, float[] weights) Calculates the weighted impurity of the targets specified in the indices array.- Parameters:
indices
- The indices in the targets and weights arrays.targets
- The regression targets.weights
- The example weights.- Returns:
- The weighted impurity.
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impurity
Calculates the weighted impurity of the targets specified in the indices container.- Parameters:
indices
- The indices in the targets and weights arrays.targets
- The regression targets.weights
- The example weights.- Returns:
- The weighted impurity.
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