org.apache.spark.ml.regression
Class GBTRegressionModel

Object
  extended by org.apache.spark.ml.PipelineStage
      extended by org.apache.spark.ml.Transformer
          extended by org.apache.spark.ml.Model<M>
              extended by org.apache.spark.ml.PredictionModel<Vector,GBTRegressionModel>
                  extended by org.apache.spark.ml.regression.GBTRegressionModel
All Implemented Interfaces:
java.io.Serializable, Logging, Params

public final class GBTRegressionModel
extends PredictionModel<Vector,GBTRegressionModel>
implements scala.Serializable

:: Experimental ::

Gradient-Boosted Trees (GBTs) model for regression. It supports both continuous and categorical features. param: _trees Decision trees in the ensemble. param: _treeWeights Weights for the decision trees in the ensemble.

See Also:
Serialized Form

Constructor Summary
GBTRegressionModel(String uid, DecisionTreeRegressionModel[] _trees, double[] _treeWeights)
           
 
Method Summary
 GBTRegressionModel copy(ParamMap extra)
          Creates a copy of this instance with the same UID and some extra params.
static GBTRegressionModel fromOld(GradientBoostedTreesModel oldModel, GBTRegressor parent, scala.collection.immutable.Map<Object,Object> categoricalFeatures)
          (private[ml]) Convert a model from the old API
 String toString()
           
 org.apache.spark.ml.tree.DecisionTreeModel[] trees()
           
 double[] treeWeights()
           
 String uid()
           
 StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
          Validates and transforms the input schema with the provided param map.
 
Methods inherited from class org.apache.spark.ml.PredictionModel
setFeaturesCol, setPredictionCol, transform, transformSchema
 
Methods inherited from class org.apache.spark.ml.Model
hasParent, parent, setParent
 
Methods inherited from class org.apache.spark.ml.Transformer
transform, transform, transform
 
Methods inherited from class Object
equals, getClass, hashCode, notify, notifyAll, wait, wait, wait
 
Methods inherited from interface org.apache.spark.ml.param.Params
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, setDefault, shouldOwn, validateParams
 
Methods inherited from interface org.apache.spark.Logging
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
 

Constructor Detail

GBTRegressionModel

public GBTRegressionModel(String uid,
                          DecisionTreeRegressionModel[] _trees,
                          double[] _treeWeights)
Method Detail

fromOld

public static GBTRegressionModel fromOld(GradientBoostedTreesModel oldModel,
                                         GBTRegressor parent,
                                         scala.collection.immutable.Map<Object,Object> categoricalFeatures)
(private[ml]) Convert a model from the old API


uid

public String uid()

trees

public org.apache.spark.ml.tree.DecisionTreeModel[] trees()

treeWeights

public double[] treeWeights()

copy

public GBTRegressionModel copy(ParamMap extra)
Description copied from interface: Params
Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly.

Specified by:
copy in interface Params
Specified by:
copy in class Model<GBTRegressionModel>
Parameters:
extra - (undocumented)
Returns:
(undocumented)
See Also:
defaultCopy()

toString

public String toString()
Overrides:
toString in class Object

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                             boolean fitting,
                                             DataType featuresDataType)
Validates and transforms the input schema with the provided param map.

Parameters:
schema - input schema
fitting - whether this is in fitting
featuresDataType - SQL DataType for FeaturesType. E.g., VectorUDT for vector features.
Returns:
output schema