Package | Description |
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org.tribuo.regression.rtree |
Provides an implementation of decision trees for regression problems.
|
org.tribuo.regression.rtree.impl |
Provides internal implementation classes for the regression trees.
|
org.tribuo.regression.rtree.impurity |
Provides implementations of regression tree impurity metrics.
|
Constructor and Description |
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CARTJointRegressionTrainer(int maxDepth,
float minChildWeight,
float minImpurityDecrease,
float fractionFeaturesInSplit,
boolean useRandomSplitPoints,
RegressorImpurity impurity,
boolean normalize,
long seed)
Creates a CART Trainer.
|
CARTJointRegressionTrainer(int maxDepth,
float minChildWeight,
float minImpurityDecrease,
float fractionFeaturesInSplit,
RegressorImpurity impurity,
boolean normalize,
long seed)
Creates a CART Trainer.
|
CARTRegressionTrainer(int maxDepth,
float minChildWeight,
float minImpurityDecrease,
float fractionFeaturesInSplit,
boolean useRandomSplitPoints,
RegressorImpurity impurity,
long seed)
Creates a CART Trainer.
|
CARTRegressionTrainer(int maxDepth,
float minChildWeight,
float minImpurityDecrease,
float fractionFeaturesInSplit,
RegressorImpurity impurity,
long seed)
Creates a CART Trainer.
|
Constructor and Description |
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JointRegressorTrainingNode(RegressorImpurity impurity,
Dataset<Regressor> examples,
boolean normalize,
AbstractTrainingNode.LeafDeterminer leafDeterminer)
Constructor which creates the inverted file.
|
RegressorTrainingNode(RegressorImpurity impurity,
RegressorTrainingNode.InvertedData tuple,
int dimIndex,
String dimName,
int numExamples,
ImmutableFeatureMap featureIDMap,
ImmutableOutputInfo<Regressor> outputInfo,
AbstractTrainingNode.LeafDeterminer leafDeterminer) |
Modifier and Type | Class and Description |
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class |
MeanAbsoluteError
Measures the mean absolute error over a set of inputs.
|
class |
MeanSquaredError
Measures the mean squared error over a set of inputs.
|
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