Class: GBTRegressor

eclairjs/ml/regression.GBTRegressor

[[http://en.wikipedia.org/wiki/Gradient_boosting Gradient-Boosted Trees (GBTs)]] learning algorithm for regression. It supports both continuous and categorical features. The implementation is based upon: J.H. Friedman. "Stochastic Gradient Boosting." 1999. Notes on Gradient Boosting vs. TreeBoost: - This implementation is for Stochastic Gradient Boosting, not for TreeBoost. - Both algorithms learn tree ensembles by minimizing loss functions. - TreeBoost (Friedman, 1999) additionally modifies the outputs at tree leaf nodes based on the loss function, whereas the original gradient boosting method does not. - When the loss is SquaredError, these methods give the same result, but they could differ for other loss functions. - We expect to implement TreeBoost in the future: [https://issues.apache.org/jira/browse/SPARK-4240]

Constructor

new GBTRegressor(uidopt)

Parameters:
Name Type Attributes Description
uid string <optional>
Source:

Extends

Methods

(static) load(path) → {GBTRegressor}

Parameters:
Name Type Description
path string
Source:
Returns:
Type
GBTRegressor

copy(extra) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
extra module:eclairjs/ml/param.ParamMap
Overrides:
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

extractParamMap() → {module:eclairjs/ml/param.ParamMap}

Inherited From:
Source:
Returns:
Type
module:eclairjs/ml/param.ParamMap

fit(dataset) → {module:eclairjs/ml/regression.GBTRegressionModel}

Parameters:
Name Type Description
dataset module:eclairjs/sql.DataFrame
Overrides:
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressionModel

setCacheNodeIds(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value boolean
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setCheckpointInterval(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setFeaturesCol(value) → {module:eclairjs/ml.Predictor}

Parameters:
Name Type Description
value string
Inherited From:
Source:
Returns:
Type
module:eclairjs/ml.Predictor

setImpurity(value) → {module:eclairjs/ml/regression.GBTRegressor}

The impurity setting is ignored for GBT models. Individual trees are built using impurity "Variance."
Parameters:
Name Type Description
value string
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setLabelCol(value) → {module:eclairjs/ml.Predictor}

Parameters:
Name Type Description
value string
Inherited From:
Source:
Returns:
Type
module:eclairjs/ml.Predictor

setLossType(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value string
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setMaxBins(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setMaxDepth(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setMaxIter(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setMaxMemoryInMB(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setMinInfoGain(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setMinInstancesPerNode(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setPredictionCol(value) → {module:eclairjs/ml.Predictor}

Parameters:
Name Type Description
value string
Inherited From:
Source:
Returns:
Type
module:eclairjs/ml.Predictor

setSeed(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setStepSize(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

setSubsamplingRate(value) → {module:eclairjs/ml/regression.GBTRegressor}

Parameters:
Name Type Description
value number
Source:
Returns:
Type
module:eclairjs/ml/regression.GBTRegressor

transformSchema(schema) → {module:eclairjs/sql/types.StructType}

Parameters:
Name Type Description
schema module:eclairjs/sql/types.StructType
Inherited From:
Source:
Returns:
Type
module:eclairjs/sql/types.StructType

uid() → {Promise.<string>}

An immutable unique ID for the object and its derivatives.
Source:
Returns:
Type
Promise.<string>