public final class DecisionTreeRegressor extends Predictor<Vector,DecisionTreeRegressor,DecisionTreeRegressionModel>
Decision tree
learning algorithm
for regression.
It supports both continuous and categorical features.Constructor and Description |
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DecisionTreeRegressor() |
DecisionTreeRegressor(String uid) |
Modifier and Type | Method and Description |
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DecisionTreeRegressor |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
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Param<String> |
featuresCol()
Param for features column name.
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String |
getFeaturesCol() |
String |
getLabelCol() |
String |
getPredictionCol() |
Param<String> |
labelCol()
Param for label column name.
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Param<String> |
predictionCol()
Param for prediction column name.
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DecisionTreeRegressor |
setCacheNodeIds(boolean value) |
DecisionTreeRegressor |
setCheckpointInterval(int value) |
DecisionTreeRegressor |
setImpurity(String value) |
DecisionTreeRegressor |
setMaxBins(int value) |
DecisionTreeRegressor |
setMaxDepth(int value) |
DecisionTreeRegressor |
setMaxMemoryInMB(int value) |
DecisionTreeRegressor |
setMinInfoGain(double value) |
DecisionTreeRegressor |
setMinInstancesPerNode(int value) |
DecisionTreeRegressor |
setSeed(long value) |
static String[] |
supportedImpurities()
Accessor for supported impurities: variance
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String |
uid()
An immutable unique ID for the object and its derivatives.
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StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType)
Validates and transforms the input schema with the provided param map.
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fit, setFeaturesCol, setLabelCol, setPredictionCol, transformSchema
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams
toString
initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
public DecisionTreeRegressor(String uid)
public DecisionTreeRegressor()
public static final String[] supportedImpurities()
public String uid()
Identifiable
public DecisionTreeRegressor setMaxDepth(int value)
public DecisionTreeRegressor setMaxBins(int value)
public DecisionTreeRegressor setMinInstancesPerNode(int value)
public DecisionTreeRegressor setMinInfoGain(double value)
public DecisionTreeRegressor setMaxMemoryInMB(int value)
public DecisionTreeRegressor setCacheNodeIds(boolean value)
public DecisionTreeRegressor setCheckpointInterval(int value)
public DecisionTreeRegressor setImpurity(String value)
public DecisionTreeRegressor setSeed(long value)
public DecisionTreeRegressor copy(ParamMap extra)
Params
copy
in interface Params
copy
in class Predictor<Vector,DecisionTreeRegressor,DecisionTreeRegressionModel>
extra
- (undocumented)defaultCopy()
public 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.public Param<String> labelCol()
public String getLabelCol()
public Param<String> featuresCol()
public String getFeaturesCol()
public Param<String> predictionCol()
public String getPredictionCol()