com.sas.cas.actions.decisionTree

Class GbtreeTrainOptions

java.lang.Object

com.sas.cas.CASActionOptions

com.sas.cas.CASGeneratedActionOptions

com.sas.cas.actions.decisionTree.GbtreeTrainOptions

All Implemented Interfaces:

KeyedMap<java.lang.String,java.lang.Object>, java.io.Serializable, java.util.Map<java.lang.String,java.lang.Object>

public class GbtreeTrainOptions
extends CASGeneratedActionOptions

Options for gbtreeTrain: Train a gradient boosting tree.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	GbtreeTrainOptions.DISTRIBUTION
static class	GbtreeTrainOptions.MISSING

Nested classes/interfaces inherited from class com.sas.cas.CASActionOptions

CASActionOptions.EnumValue, CASActionOptions.FORMAT

Nested classes/interfaces inherited from interface java.util.Map

java.util.Map.Entry<K,V>

Field Summary

Fields

Modifier and Type	Field and Description
static java.lang.String	ACTION_NAME
static java.lang.String	ACTION_SET_NAME
static java.lang.String	KEY_ATTRIBUTES
static java.lang.String	KEY_BINORDER
static java.lang.String	KEY_CASOUT
static java.lang.String	KEY_CODE
static java.lang.String	KEY_DISTRIBUTION
static java.lang.String	KEY_EARLYSTOP
static java.lang.String	KEY_GREEDY
static java.lang.String	KEY_INCLUDEMISSING
static java.lang.String	KEY_INPUTS
static java.lang.String	KEY_LASSO
static java.lang.String	KEY_LEAFSIZE
static java.lang.String	KEY_LEARNINGRATE
static java.lang.String	KEY_M
static java.lang.String	KEY_MAXBRANCH
static java.lang.String	KEY_MAXLEVEL
static java.lang.String	KEY_MERGEBIN
static java.lang.String	KEY_MINUSEINSEARCH
static java.lang.String	KEY_MISSING
static java.lang.String	KEY_MODELID
static java.lang.String	KEY_NBINS
static java.lang.String	KEY_NOMINALS
static java.lang.String	KEY_NTREE
static java.lang.String	KEY_RIDGE
static java.lang.String	KEY_SEED
static java.lang.String	KEY_SINGULAR
static java.lang.String	KEY_SUBSAMPLERATE
static java.lang.String	KEY_TABLE
static java.lang.String	KEY_TARGET
static java.lang.String	KEY_VALIDTABLE
static java.lang.String	KEY_VARIMP
static java.lang.String	KEY_WEIGHT

Fields inherited from class com.sas.cas.CASActionOptions

FLAGS_EXPAND_ARRAYS, FLAGS_IGNORE_DISPOSITION_ERROR, FLAGS_RETURN_RESULTS_ON_EXCEPTION, FLAGS_SKIP_ACTION_EVENTS, FLAGS_SKIP_RESULTS, HIDDEN_PASSWORD, JSON_NULL, LUA_NIL, PARAMETER_FLAG_ISPASSWORD, PARAMETER_FLAG_ISPATH, PARAMETER_FLAG_ISTABLENAME, PARAMETER_FLAG_ISVAR, PARAMETER_FLAG_REQUIRED, PYTHON_NULL, SERIALIZED_PREFIX

Constructor Summary

Constructors

Constructor and Description
GbtreeTrainOptions()
GbtreeTrainOptions(CASActionOptions options)

Method Summary

Modifier and Type	Method and Description
Casinvardesc[]	getAttr()
Casinvardesc[]	getAttribute()
Casinvardesc[]	getAttributes()
Casinvardesc[]	getAttrs()
java.lang.Boolean	getBinOrder()
Casouttable	getCasOut()
Codegen	getCode()
java.lang.Object	getDistribution()
Tkcasdt_earlyStop	getEarlyStop()
java.lang.Boolean	getGreedy()
java.lang.Boolean	getIncludeMissing()
Casinvardesc[]	getInput()
Casinvardesc[]	getInputs()
java.lang.Double	getLasso()
java.lang.Integer	getLeafSize()
java.lang.Double	getLearningRate()
java.lang.Integer	getM()
java.lang.Integer	getMaxBranch()
java.lang.Integer	getMaxLevel()
java.lang.Boolean	getMergeBin()
java.lang.Integer	getMinUseInSearch()
GbtreeTrainOptions.MISSING	getMissing()
java.lang.String	getModelId()
java.lang.Integer	getNBins()
Casinvardesc[]	getNominal()
Casinvardesc[]	getNominals()
java.lang.Integer	getNTree()
java.lang.Double	getRidge()
java.lang.Double	getSamplingRate()
java.lang.Double	getSeed()
java.lang.Object	getServerDefaultValue(java.lang.String key) Gets the server default value, if known.
java.lang.Double	getSingular()
java.lang.Double	getSubsample()
java.lang.Double	getSubSampleRate()
Castable	getTable()
java.lang.String	getTarget()
Castable	getValidTable()
Casinvardesc[]	getVarAttrs()
java.lang.Boolean	getVarImp()
java.lang.String	getWeight()
GbtreeTrainOptions	setAttr(Casinvardesc[] value)
GbtreeTrainOptions	setAttribute(Casinvardesc[] value)
GbtreeTrainOptions	setAttributes(Casinvardesc[] value) Sets the value of parameter 'attributes': specifies temporary attributes, such as a format, to apply to input variables.
GbtreeTrainOptions	setAttrs(Casinvardesc[] value)
GbtreeTrainOptions	setBinOrder(java.lang.Boolean value) Sets the value of parameter 'binOrder': by default, the bin order is preserved for numeric variables.
GbtreeTrainOptions	setCasOut(Casouttable value) Sets the value of parameter 'casOut': specifies the table to store the decision tree model in.
GbtreeTrainOptions	setCode(Codegen value) Sets the value of parameter 'code': requests that the action produce SAS score code.
GbtreeTrainOptions	setDistribution(GbtreeTrainOptions.DISTRIBUTION value) Sets the value of parameter 'distribution' for alternative 1.
GbtreeTrainOptions	setDistribution(java.lang.Long value) Sets the value of parameter 'distribution' for alternative 2.
GbtreeTrainOptions	setEarlyStop(Tkcasdt_earlyStop value) Sets the value of parameter 'earlyStop'.
GbtreeTrainOptions	setGreedy(java.lang.Boolean value) Sets the value of parameter 'greedy': by default, a greedy search or exhaustive search is used to determine the best split for each variable of each tree node.
GbtreeTrainOptions	setIncludeMissing(java.lang.Boolean value) Sets the value of parameter 'includeMissing': by default, observations with missing values are included.
GbtreeTrainOptions	setInput(Casinvardesc[] value)
GbtreeTrainOptions	setInputs(Casinvardesc[] value) Sets the value of parameter 'inputs': specifies the input variables to use in the analysis.
GbtreeTrainOptions	setLasso(java.lang.Double value) Sets the value of parameter 'lasso': specifies the L1 norm regularization on prediction.
GbtreeTrainOptions	setLeafSize(java.lang.Integer value) Sets the value of parameter 'leafSize': specifies the minimum number of observations on each node.
GbtreeTrainOptions	setLearningRate(java.lang.Double value) Sets the value of parameter 'learningRate': specifies the learning rate of each tree.
GbtreeTrainOptions	setM(java.lang.Integer value) Sets the value of parameter 'm': specifies the number of input variables to consider for splitting on a node.
GbtreeTrainOptions	setMaxBranch(java.lang.Integer value) Sets the value of parameter 'maxBranch': specifies the maximum number of children (branches) allowed for each level of the tree.
GbtreeTrainOptions	setMaxLevel(java.lang.Integer value) Sets the value of parameter 'maxLevel': specifies the maximum number of the tree level.
GbtreeTrainOptions	setMergeBin(java.lang.Boolean value) Sets the value of parameter 'mergeBin': by default, when the largest value in one bin matches the lowest value in a neighboring bin, the values are merged into the lower bin.
GbtreeTrainOptions	setMinUseInSearch(java.lang.Integer value) Sets the value of parameter 'minUseInSearch': specifies a threshold for utilizing missing values in the split search when the missing parameter is set to USEINSEARCH.
GbtreeTrainOptions	setMissing(GbtreeTrainOptions.MISSING value) Sets the value of parameter 'missing': specifies the missing policy to handle missing values.
GbtreeTrainOptions	setModelId(java.lang.String value) Sets the value of parameter 'modelId': specifies the model ID variable name to use when generating SAS score code.
GbtreeTrainOptions	setNBins(java.lang.Integer value) Sets the value of parameter 'nBins': specifies the number of bins to use for numeric variables in the calculation of the decision tree.
GbtreeTrainOptions	setNominal(Casinvardesc[] value)
GbtreeTrainOptions	setNominals(Casinvardesc[] value) Sets the value of parameter 'nominals': specifies the nominal input variables to use in the analysis.
GbtreeTrainOptions	setNTree(java.lang.Integer value) Sets the value of parameter 'nTree': specifies the number of trees to create.
GbtreeTrainOptions	setRidge(java.lang.Double value) Sets the value of parameter 'ridge': specifies the L2 norm regularization on prediction.
GbtreeTrainOptions	setSamplingRate(java.lang.Double value)
GbtreeTrainOptions	setSeed(java.lang.Double value) Sets the value of parameter 'seed': specifies the seed for the random number generator.
GbtreeTrainOptions	setSingular(java.lang.Double value) Sets the value of parameter 'singular': specifies a small value to avoid zero in division.
GbtreeTrainOptions	setSubsample(java.lang.Double value)
GbtreeTrainOptions	setSubSampleRate(java.lang.Double value) Sets the value of parameter 'subSampleRate': specifies the fraction of the data to use for building each tree.
GbtreeTrainOptions	setTable(Castable value) Sets the value of parameter 'table': specifies the settings for an input table.
GbtreeTrainOptions	setTarget(java.lang.String value) Sets the value of parameter 'target': specifies the target or response variable for training the decision tree.
GbtreeTrainOptions	setValidTable(Castable value) Sets the value of parameter 'validTable': specifies the settings for an input table.
GbtreeTrainOptions	setVarAttrs(Casinvardesc[] value)
GbtreeTrainOptions	setVarImp(java.lang.Boolean value) Sets the value of parameter 'varImp': specifies whether the variable importance information is generated.
GbtreeTrainOptions	setWeight(java.lang.String value) Sets the value of parameter 'weight': specifies a numeric variable that contains the weight of each observation.

Methods inherited from class com.sas.cas.CASActionOptions

addActionFlags, addParameterFlag, appendValue, checkForPasswords, clear, containsKey, containsValue, convertToEnumArray, copy, deserialize, entrySet, equals, findOptionsClass, findSetter, get, getActionFlags, getActionName, getActionResponseEventListener, getActionResultEventListener, getActionSetName, getCASClient, getClassName, getDebugOptions, getDispositionEventListener, getFullyQualifiedActionName, getLogEventListener, getLogMessage, getMessageOutputStream, getMessageTagHandler, getParameter, getParameterAsBoolean, getParameterAsByteArray, getParameterAsDouble, getParameterAsDoubleArray, getParameterAsInteger, getParameterAsIntegerArray, getParameterAsLong, getParameterAsLongArray, getParameterAsString, getParameterAsStringArray, getParameterFlags, getParameterIgnoreCase, getParameterIgnoreCase, getParameterKeys, getPerformanceEventListener, getPropertyKey, getSessionID, getUserProperty, getUserPropertyKeys, hashCode, invoke, isEmpty, isFlagSet, isMap, isParameterFlagSet, isPassword, isPath, isRequired, isTable, isVariable, keySet, put, putAll, putAllDeep, putDeep, putDeep, quoteIfNotNull, remove, removeParameter, set, setActionFlags, setActionName, setActionResponseEventListener, setActionResultEventListener, setActionSetName, setCASClient, setDebugOptions, setDispositionEventListener, setFullyQualifiedActionName, setLogEventListener, setLogMessage, setMessageOutputStream, setMessageTagHandler, setParameter, setPerformanceEventListener, setPropertyKey, setSessionID, setUserProperty, size, toCASLString, toLuaString, toLuaString, toOptionsWithGeneratedClasses, toSerialized, toString, toString, toString, upcaseFirstChar, values

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, forEach, getOrDefault, merge, putIfAbsent, remove, replace, replace, replaceAll

Field Detail

ACTION_SET_NAME

public static final java.lang.String ACTION_SET_NAME

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Constant Field Values

ACTION_NAME

public static final java.lang.String ACTION_NAME

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Constant Field Values

KEY_TABLE

public static final java.lang.String KEY_TABLE

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Constant Field Values

KEY_TARGET

public static final java.lang.String KEY_TARGET

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Constant Field Values

KEY_INPUTS

public static final java.lang.String KEY_INPUTS

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Constant Field Values

KEY_NOMINALS

public static final java.lang.String KEY_NOMINALS

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Constant Field Values

KEY_ATTRIBUTES

public static final java.lang.String KEY_ATTRIBUTES

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Constant Field Values

KEY_WEIGHT

public static final java.lang.String KEY_WEIGHT

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Constant Field Values

KEY_VALIDTABLE

public static final java.lang.String KEY_VALIDTABLE

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Constant Field Values

KEY_NBINS

public static final java.lang.String KEY_NBINS

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Constant Field Values

KEY_MAXLEVEL

public static final java.lang.String KEY_MAXLEVEL

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Constant Field Values

KEY_MAXBRANCH

public static final java.lang.String KEY_MAXBRANCH

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Constant Field Values

KEY_LEAFSIZE

public static final java.lang.String KEY_LEAFSIZE

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Constant Field Values

KEY_MISSING

public static final java.lang.String KEY_MISSING

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Constant Field Values

KEY_MINUSEINSEARCH

public static final java.lang.String KEY_MINUSEINSEARCH

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Constant Field Values

KEY_GREEDY

public static final java.lang.String KEY_GREEDY

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Constant Field Values

KEY_BINORDER

public static final java.lang.String KEY_BINORDER

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Constant Field Values

KEY_VARIMP

public static final java.lang.String KEY_VARIMP

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Constant Field Values

KEY_CODE

public static final java.lang.String KEY_CODE

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Constant Field Values

KEY_MODELID

public static final java.lang.String KEY_MODELID

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Constant Field Values

KEY_CASOUT

public static final java.lang.String KEY_CASOUT

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Constant Field Values

KEY_MERGEBIN

public static final java.lang.String KEY_MERGEBIN

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Constant Field Values

KEY_INCLUDEMISSING

public static final java.lang.String KEY_INCLUDEMISSING

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Constant Field Values

KEY_NTREE

public static final java.lang.String KEY_NTREE

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KEY_SEED

public static final java.lang.String KEY_SEED

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Constant Field Values

KEY_LEARNINGRATE

public static final java.lang.String KEY_LEARNINGRATE

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Constant Field Values

KEY_SUBSAMPLERATE

public static final java.lang.String KEY_SUBSAMPLERATE

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Constant Field Values

KEY_DISTRIBUTION

public static final java.lang.String KEY_DISTRIBUTION

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Constant Field Values

KEY_M

public static final java.lang.String KEY_M

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Constant Field Values

KEY_LASSO

public static final java.lang.String KEY_LASSO

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KEY_RIDGE

public static final java.lang.String KEY_RIDGE

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KEY_SINGULAR

public static final java.lang.String KEY_SINGULAR

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KEY_EARLYSTOP

public static final java.lang.String KEY_EARLYSTOP

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Constant Field Values

Constructor Detail

GbtreeTrainOptions

public GbtreeTrainOptions()

GbtreeTrainOptions

public GbtreeTrainOptions(CASActionOptions options)

Method Detail

getServerDefaultValue

public java.lang.Object getServerDefaultValue(java.lang.String key)

Description copied from class: CASActionOptions

Gets the server default value, if known.

Overrides:

getServerDefaultValue in class CASActionOptions

Parameters:

key - The parameter key

Returns:

THe default value, or null if not known

getTable

public Castable getTable()

setTable

public GbtreeTrainOptions setTable(Castable value)

Sets the value of parameter 'table': specifies the settings for an input table.

Parameters:

value - The value

Returns:

The options object

getTarget

public java.lang.String getTarget()

setTarget

public GbtreeTrainOptions setTarget(java.lang.String value)

Sets the value of parameter 'target': specifies the target or response variable for training the decision tree. If the variable is numeric, but not specified in normal=, and nbinstarget= is not specified, then a regression tree is trained.

Parameters:

value - The value

Returns:

The options object

getInputs

public Casinvardesc[] getInputs()

getInput

public Casinvardesc[] getInput()

setInputs

public GbtreeTrainOptions setInputs(Casinvardesc[] value)

Sets the value of parameter 'inputs': specifies the input variables to use in the analysis.

Parameters:

value - The value

Returns:

The options object

setInput

public GbtreeTrainOptions setInput(Casinvardesc[] value)

getNominals

public Casinvardesc[] getNominals()

getNominal

public Casinvardesc[] getNominal()

setNominals

public GbtreeTrainOptions setNominals(Casinvardesc[] value)

Sets the value of parameter 'nominals': specifies the nominal input variables to use in the analysis.

Parameters:

value - The value

Returns:

The options object

setNominal

public GbtreeTrainOptions setNominal(Casinvardesc[] value)

getAttributes

public Casinvardesc[] getAttributes()

getAttribute

public Casinvardesc[] getAttribute()

getAttrs

public Casinvardesc[] getAttrs()

getAttr

public Casinvardesc[] getAttr()

getVarAttrs

public Casinvardesc[] getVarAttrs()

setAttributes

public GbtreeTrainOptions setAttributes(Casinvardesc[] value)

Sets the value of parameter 'attributes': specifies temporary attributes, such as a format, to apply to input variables.

Parameters:

value - The value

Returns:

The options object

setAttribute

public GbtreeTrainOptions setAttribute(Casinvardesc[] value)

setAttrs

public GbtreeTrainOptions setAttrs(Casinvardesc[] value)

setAttr

public GbtreeTrainOptions setAttr(Casinvardesc[] value)

setVarAttrs

public GbtreeTrainOptions setVarAttrs(Casinvardesc[] value)

getWeight

public java.lang.String getWeight()

setWeight

public GbtreeTrainOptions setWeight(java.lang.String value)

Sets the value of parameter 'weight': specifies a numeric variable that contains the weight of each observation.

Parameters:

value - The value

Returns:

The options object

getValidTable

public Castable getValidTable()

setValidTable

public GbtreeTrainOptions setValidTable(Castable value)

Sets the value of parameter 'validTable': specifies the settings for an input table.

Parameters:

value - The value

Returns:

The options object

getNBins

public java.lang.Integer getNBins()

setNBins

public GbtreeTrainOptions setNBins(java.lang.Integer value)

Sets the value of parameter 'nBins': specifies the number of bins to use for numeric variables in the calculation of the decision tree. The server default is 20.

Parameters:

value - The value

Returns:

The options object

getMaxLevel

public java.lang.Integer getMaxLevel()

setMaxLevel

public GbtreeTrainOptions setMaxLevel(java.lang.Integer value)

Sets the value of parameter 'maxLevel': specifies the maximum number of the tree level. The server default is 6.

Parameters:

value - The value

Returns:

The options object

getMaxBranch

public java.lang.Integer getMaxBranch()

setMaxBranch

public GbtreeTrainOptions setMaxBranch(java.lang.Integer value)

Sets the value of parameter 'maxBranch': specifies the maximum number of children (branches) allowed for each level of the tree. The server default is 2.

Parameters:

value - The value

Returns:

The options object

getLeafSize

public java.lang.Integer getLeafSize()

setLeafSize

public GbtreeTrainOptions setLeafSize(java.lang.Integer value)

Sets the value of parameter 'leafSize': specifies the minimum number of observations on each node. The server default is 5.

Parameters:

value - The value

Returns:

The options object

getMissing

public GbtreeTrainOptions.MISSING getMissing()

setMissing

public GbtreeTrainOptions setMissing(GbtreeTrainOptions.MISSING value)

Sets the value of parameter 'missing': specifies the missing policy to handle missing values. The server default is MISSING.MACSMALL.

Parameters:

value - The value

Returns:

The options object

getMinUseInSearch

public java.lang.Integer getMinUseInSearch()

setMinUseInSearch

public GbtreeTrainOptions setMinUseInSearch(java.lang.Integer value)

Sets the value of parameter 'minUseInSearch': specifies a threshold for utilizing missing values in the split search when the missing parameter is set to USEINSEARCH. If the number of observations in which the splitting variable has missing values in a node is greater than or equal to the specified value, then the action initiates the USEINSEARCH policy. Otherwise, the missing values are assigned to a popular branch. The server default is 1.

Parameters:

value - The value

Returns:

The options object

getGreedy

public java.lang.Boolean getGreedy()

setGreedy

public GbtreeTrainOptions setGreedy(java.lang.Boolean value)

Sets the value of parameter 'greedy': by default, a greedy search or exhaustive search is used to determine the best split for each variable of each tree node. When set to False, a fast and efficient algorithm that is based on clustering is applied. Setting this parameter to False is recommended for variables with high cardinality. The server default is TRUE.

Parameters:

value - The value

Returns:

The options object

getBinOrder

public java.lang.Boolean getBinOrder()

setBinOrder

public GbtreeTrainOptions setBinOrder(java.lang.Boolean value)

Sets the value of parameter 'binOrder': by default, the bin order is preserved for numeric variables. When set to False, the bin order is ignored for numeric variables. The server default is TRUE.

Parameters:

value - The value

Returns:

The options object

getVarImp

public java.lang.Boolean getVarImp()

setVarImp

public GbtreeTrainOptions setVarImp(java.lang.Boolean value)

Sets the value of parameter 'varImp': specifies whether the variable importance information is generated. The importance value is determined by the total Gini reduction. The server default is FALSE.

Parameters:

value - The value

Returns:

The options object

getCode

public Codegen getCode()

setCode

public GbtreeTrainOptions setCode(Codegen value)

Sets the value of parameter 'code': requests that the action produce SAS score code. Specify additional parameters.

Parameters:

value - The value

Returns:

The options object

getModelId

public java.lang.String getModelId()

setModelId

public GbtreeTrainOptions setModelId(java.lang.String value)

Sets the value of parameter 'modelId': specifies the model ID variable name to use when generating SAS score code. By default, DT_ is prefixed to the target variable name.

Parameters:

value - The value

Returns:

The options object

getCasOut

public Casouttable getCasOut()

setCasOut

public GbtreeTrainOptions setCasOut(Casouttable value)

Sets the value of parameter 'casOut': specifies the table to store the decision tree model in. When not specified, a random name is generated.

Parameters:

value - The value

Returns:

The options object

getMergeBin

public java.lang.Boolean getMergeBin()

setMergeBin

public GbtreeTrainOptions setMergeBin(java.lang.Boolean value)

Sets the value of parameter 'mergeBin': by default, when the largest value in one bin matches the lowest value in a neighboring bin, the values are merged into the lower bin. When set to False, the action does not try to merge bins. The server default is TRUE.

Parameters:

value - The value

Returns:

The options object

getIncludeMissing

public java.lang.Boolean getIncludeMissing()

setIncludeMissing

public GbtreeTrainOptions setIncludeMissing(java.lang.Boolean value)

Sets the value of parameter 'includeMissing': by default, observations with missing values are included. When set to False, observations with missing values for the variables used in the tree model are ignored when scoring. The server default is TRUE.

Parameters:

value - The value

Returns:

The options object

getNTree

public java.lang.Integer getNTree()

setNTree

public GbtreeTrainOptions setNTree(java.lang.Integer value)

Sets the value of parameter 'nTree': specifies the number of trees to create. The server default is 50.

Parameters:

value - The value

Returns:

The options object

getSeed

public java.lang.Double getSeed()

setSeed

public GbtreeTrainOptions setSeed(java.lang.Double value)

Sets the value of parameter 'seed': specifies the seed for the random number generator. By default, the random number stream is based on the computer clock. Negative values also result in random number streams based on the computer clock. If you want a reproducible random number sequence between runs, specify a value that is greater than zero. The server default is 0.

Parameters:

value - The value

Returns:

The options object

getLearningRate

public java.lang.Double getLearningRate()

setLearningRate

public GbtreeTrainOptions setLearningRate(java.lang.Double value)

Sets the value of parameter 'learningRate': specifies the learning rate of each tree. The server default is 0.1.

Parameters:

value - The value

Returns:

The options object

getSubSampleRate

public java.lang.Double getSubSampleRate()

getSubsample

public java.lang.Double getSubsample()

getSamplingRate

public java.lang.Double getSamplingRate()

setSubSampleRate

public GbtreeTrainOptions setSubSampleRate(java.lang.Double value)

Sets the value of parameter 'subSampleRate': specifies the fraction of the data to use for building each tree. The server default is 0.5.

Parameters:

value - The value

Returns:

The options object

setSubsample

public GbtreeTrainOptions setSubsample(java.lang.Double value)

setSamplingRate

public GbtreeTrainOptions setSamplingRate(java.lang.Double value)

getDistribution

public java.lang.Object getDistribution()

setDistribution

public GbtreeTrainOptions setDistribution(GbtreeTrainOptions.DISTRIBUTION value)

Sets the value of parameter 'distribution' for alternative 1. The server default is DISTRIBUTION.BINARY.

Parameters:

value - The value

Returns:

The options object

setDistribution

public GbtreeTrainOptions setDistribution(java.lang.Long value)

Sets the value of parameter 'distribution' for alternative 2.

Parameters:

value - The value

Returns:

The options object

getM

public java.lang.Integer getM()

setM

public GbtreeTrainOptions setM(java.lang.Integer value)

Sets the value of parameter 'm': specifies the number of input variables to consider for splitting on a node. The variables are selected at random from the input variables for each tree. By default, forest uses the square root of the number of input variables is used, rounded up to the nearest integer. For gradient boosting tree, the number of input variables is used.

Parameters:

value - The value

Returns:

The options object

getLasso

public java.lang.Double getLasso()

setLasso

public GbtreeTrainOptions setLasso(java.lang.Double value)

Sets the value of parameter 'lasso': specifies the L1 norm regularization on prediction. The value must be greater than zero. The server default is 0.

Parameters:

value - The value

Returns:

The options object

getRidge

public java.lang.Double getRidge()

setRidge

public GbtreeTrainOptions setRidge(java.lang.Double value)

Sets the value of parameter 'ridge': specifies the L2 norm regularization on prediction. The value must be greater than zero. The server default is 0.

Parameters:

value - The value

Returns:

The options object

getSingular

public java.lang.Double getSingular()

setSingular

public GbtreeTrainOptions setSingular(java.lang.Double value)

Sets the value of parameter 'singular': specifies a small value to avoid zero in division. The server default is 1e-12.

Parameters:

value - The value

Returns:

The options object

getEarlyStop

public Tkcasdt_earlyStop getEarlyStop()

setEarlyStop

public GbtreeTrainOptions setEarlyStop(Tkcasdt_earlyStop value)

Sets the value of parameter 'earlyStop'.

Parameters:

value - The value

Returns:

The options object