public final class GBTClassificationModel extends PredictionModel<Vector,GBTClassificationModel> implements scala.Serializable
Gradient-Boosted Trees (GBTs)
model for classification.
It supports binary labels, as well as both continuous and categorical features.
Note: Multiclass labels are not currently supported.
param: _trees Decision trees in the ensemble.
param: _treeWeights Weights for the decision trees in the ensemble.| Constructor and Description |
|---|
GBTClassificationModel(String uid,
DecisionTreeRegressionModel[] _trees,
double[] _treeWeights) |
| Modifier and Type | Method and Description |
|---|---|
GBTClassificationModel |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
static GBTClassificationModel |
fromOld(GradientBoostedTreesModel oldModel,
GBTClassifier 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.
|
setFeaturesCol, setPredictionCol, transform, transformSchematransform, transform, transformclear, copyValues, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, setDefault, shouldOwn, validateParamsinitializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic GBTClassificationModel(String uid,
DecisionTreeRegressionModel[] _trees,
double[] _treeWeights)
public static GBTClassificationModel fromOld(GradientBoostedTreesModel oldModel, GBTClassifier parent, scala.collection.immutable.Map<Object,Object> categoricalFeatures)
public String uid()
public org.apache.spark.ml.tree.DecisionTreeModel[] trees()
public double[] treeWeights()
public GBTClassificationModel copy(ParamMap extra)
Paramscopy in interface Paramscopy in class Model<GBTClassificationModel>extra - (undocumented)public String toString()
toString in class Objectpublic StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
schema - input schemafitting - whether this is in fittingfeaturesDataType - SQL DataType for FeaturesType.
E.g., VectorUDT for vector features.