public class DecisionTreeClassifier extends ProbabilisticClassifier<Vector,DecisionTreeClassifier,DecisionTreeClassificationModel> implements DecisionTreeClassifierParams, DefaultParamsWritable
| Constructor and Description |
|---|
DecisionTreeClassifier() |
DecisionTreeClassifier(String uid) |
| Modifier and Type | Method and Description |
|---|---|
BooleanParam |
cacheNodeIds()
If false, the algorithm will pass trees to executors to match instances with nodes.
|
IntParam |
checkpointInterval()
Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
|
DecisionTreeClassifier |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
Param<String> |
impurity()
Criterion used for information gain calculation (case-insensitive).
|
Param<String> |
leafCol()
Leaf indices column name.
|
static DecisionTreeClassifier |
load(String path) |
IntParam |
maxBins()
Maximum number of bins used for discretizing continuous features and for choosing how to split
on features at each node.
|
IntParam |
maxDepth()
Maximum depth of the tree (nonnegative).
|
IntParam |
maxMemoryInMB()
Maximum memory in MB allocated to histogram aggregation.
|
DoubleParam |
minInfoGain()
Minimum information gain for a split to be considered at a tree node.
|
IntParam |
minInstancesPerNode()
Minimum number of instances each child must have after split.
|
DoubleParam |
minWeightFractionPerNode()
Minimum fraction of the weighted sample count that each child must have after split.
|
static MLReader<T> |
read() |
LongParam |
seed()
Param for random seed.
|
DecisionTreeClassifier |
setCacheNodeIds(boolean value) |
DecisionTreeClassifier |
setCheckpointInterval(int value)
Specifies how often to checkpoint the cached node IDs.
|
DecisionTreeClassifier |
setImpurity(String value) |
DecisionTreeClassifier |
setMaxBins(int value) |
DecisionTreeClassifier |
setMaxDepth(int value) |
DecisionTreeClassifier |
setMaxMemoryInMB(int value) |
DecisionTreeClassifier |
setMinInfoGain(double value) |
DecisionTreeClassifier |
setMinInstancesPerNode(int value) |
DecisionTreeClassifier |
setMinWeightFractionPerNode(double value) |
DecisionTreeClassifier |
setSeed(long value) |
DecisionTreeClassifier |
setWeightCol(String value)
Sets the value of param
weightCol. |
static String[] |
supportedImpurities()
Accessor for supported impurities: entropy, gini
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
Param<String> |
weightCol()
Param for weight column name.
|
probabilityCol, setProbabilityCol, setThresholds, thresholdsrawPredictionCol, setRawPredictionColfeaturesCol, fit, labelCol, predictionCol, setFeaturesCol, setLabelCol, setPredictionCol, transformSchemaparamsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitvalidateAndTransformSchemagetCacheNodeIds, getLeafCol, getMaxBins, getMaxDepth, getMaxMemoryInMB, getMinInfoGain, getMinInstancesPerNode, getMinWeightFractionPerNode, getOldStrategy, setLeafColgetCheckpointIntervalgetWeightColgetImpurity, getOldImpurityextractInstancesextractInstances, extractInstancesgetLabelCol, labelColfeaturesCol, getFeaturesColgetPredictionCol, predictionColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringgetRawPredictionCol, rawPredictionColgetProbabilityCol, probabilityColgetThresholds, thresholdswritesaveinitializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarningpublic DecisionTreeClassifier(String uid)
public DecisionTreeClassifier()
public static final String[] supportedImpurities()
public static DecisionTreeClassifier load(String path)
public static MLReader<T> read()
public final Param<String> impurity()
TreeClassifierParamsimpurity in interface TreeClassifierParamspublic final Param<String> leafCol()
DecisionTreeParamsleafCol in interface DecisionTreeParamspublic final IntParam maxDepth()
DecisionTreeParamsmaxDepth in interface DecisionTreeParamspublic final IntParam maxBins()
DecisionTreeParamsmaxBins in interface DecisionTreeParamspublic final IntParam minInstancesPerNode()
DecisionTreeParamsminInstancesPerNode in interface DecisionTreeParamspublic final DoubleParam minWeightFractionPerNode()
DecisionTreeParamsminWeightFractionPerNode in interface DecisionTreeParamspublic final DoubleParam minInfoGain()
DecisionTreeParamsminInfoGain in interface DecisionTreeParamspublic final IntParam maxMemoryInMB()
DecisionTreeParamsmaxMemoryInMB in interface DecisionTreeParamspublic final BooleanParam cacheNodeIds()
DecisionTreeParamscacheNodeIds in interface DecisionTreeParamspublic final Param<String> weightCol()
HasWeightColweightCol in interface HasWeightColpublic final LongParam seed()
HasSeedpublic final IntParam checkpointInterval()
HasCheckpointIntervalcheckpointInterval in interface HasCheckpointIntervalpublic String uid()
Identifiableuid in interface Identifiablepublic DecisionTreeClassifier setMaxDepth(int value)
public DecisionTreeClassifier setMaxBins(int value)
public DecisionTreeClassifier setMinInstancesPerNode(int value)
public DecisionTreeClassifier setMinWeightFractionPerNode(double value)
public DecisionTreeClassifier setMinInfoGain(double value)
public DecisionTreeClassifier setMaxMemoryInMB(int value)
public DecisionTreeClassifier setCacheNodeIds(boolean value)
public DecisionTreeClassifier setCheckpointInterval(int value)
SparkContext.
Must be at least 1.
(default = 10)value - (undocumented)public DecisionTreeClassifier setImpurity(String value)
public DecisionTreeClassifier setSeed(long value)
public DecisionTreeClassifier setWeightCol(String value)
weightCol.
If this is not set or empty, we treat all instance weights as 1.0.
Default is not set, so all instances have weight one.
value - (undocumented)public DecisionTreeClassifier copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Predictor<Vector,DecisionTreeClassifier,DecisionTreeClassificationModel>extra - (undocumented)