ForestTrainOptions (cas-client 3.2.9 API)

java.lang.Object
- com.sas.cas.CASActionOptions
- - com.sas.cas.CASGeneratedActionOptions
  - - com.sas.cas.actions.decisionTree.ForestTrainOptions

All Implemented Interfaces:

KeyedMap<java.lang.String,java.lang.Object>, java.io.Serializable, java.util.Map<java.lang.String,java.lang.Object>
```
public class ForestTrainOptions
extends CASGeneratedActionOptions
```
Options for forestTrain: Train a forest.

See Also:

Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static class ForestTrainOptions.CRIT

static class ForestTrainOptions.MISSING

static class ForestTrainOptions.VOTE
- 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>

Nested Classes
Modifier and Type	Class and Description
`static class`	`ForestTrainOptions.CRIT`
`static class`	`ForestTrainOptions.MISSING`
`static class`	`ForestTrainOptions.VOTE`

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_ALPHA`
`static java.lang.String`	`KEY_ATTRIBUTES`
`static java.lang.String`	`KEY_BINORDER`
`static java.lang.String`	`KEY_BOOTSTRAP`
`static java.lang.String`	`KEY_CASOUT`
`static java.lang.String`	`KEY_CFLEV`
`static java.lang.String`	`KEY_CODE`
`static java.lang.String`	`KEY_CRIT`
`static java.lang.String`	`KEY_EVENT`
`static java.lang.String`	`KEY_EVENTFREQ`
`static java.lang.String`	`KEY_GREEDY`
`static java.lang.String`	`KEY_INCLUDEMISSING`
`static java.lang.String`	`KEY_INPUTS`
`static java.lang.String`	`KEY_LEAFSIZE`
`static java.lang.String`	`KEY_LOH`
`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_NBINSTARGET`
`static java.lang.String`	`KEY_NOMINALS`
`static java.lang.String`	`KEY_NTREE`
`static java.lang.String`	`KEY_OOB`
`static java.lang.String`	`KEY_PRUNE`
`static java.lang.String`	`KEY_RBAIMP`
`static java.lang.String`	`KEY_SEED`
`static java.lang.String`	`KEY_TABLE`
`static java.lang.String`	`KEY_TARGET`
`static java.lang.String`	`KEY_VARIMP`
`static java.lang.String`	`KEY_VOTE`
`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

ForestTrainOptions()

ForestTrainOptions(CASActionOptions options)

Constructors
Constructor and Description
`ForestTrainOptions()`
`ForestTrainOptions(CASActionOptions options)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`java.lang.Double`	`getAlpha()`
`Casinvardesc[]`	`getAttr()`
`Casinvardesc[]`	`getAttribute()`
`Casinvardesc[]`	`getAttributes()`
`Casinvardesc[]`	`getAttrs()`
`java.lang.Boolean`	`getBinOrder()`
`java.lang.Double`	`getBootstrap()`
`Casouttable`	`getCasOut()`
`java.lang.Double`	`getCfLev()`
`Codegen`	`getCode()`
`java.lang.Object`	`getCrit()`
`java.lang.String[]`	`getEvent()`
`java.lang.Double[]`	`getEventFreq()`
`java.lang.Boolean`	`getGreedy()`
`java.lang.Boolean`	`getIncludeMissing()`
`Casinvardesc[]`	`getInput()`
`Casinvardesc[]`	`getInputs()`
`java.lang.Integer`	`getLeafSize()`
`java.lang.Integer`	`getLoh()`
`java.lang.Integer`	`getM()`
`java.lang.Integer`	`getMaxBranch()`
`java.lang.Integer`	`getMaxLevel()`
`java.lang.Boolean`	`getMergeBin()`
`java.lang.Integer`	`getMinUseInSearch()`
`ForestTrainOptions.MISSING`	`getMissing()`
`java.lang.String`	`getModelId()`
`java.lang.Integer`	`getNBins()`
`java.lang.Integer`	`getNBinsTarget()`
`Casinvardesc[]`	`getNominal()`
`Casinvardesc[]`	`getNominals()`
`java.lang.Integer`	`getNTree()`
`java.lang.Boolean`	`getOob()`
`java.lang.Boolean`	`getPrune()`
`java.lang.Boolean`	`getRbaImp()`
`java.lang.Double`	`getSeed()`
`java.lang.Object`	`getServerDefaultValue(java.lang.String key)` Gets the server default value, if known.
`Castable`	`getTable()`
`java.lang.String`	`getTarget()`
`Casinvardesc[]`	`getVarAttrs()`
`java.lang.Boolean`	`getVarImp()`
`ForestTrainOptions.VOTE`	`getVote()`
`java.lang.String`	`getWeight()`
`ForestTrainOptions`	`setAlpha(java.lang.Double value)` Sets the value of parameter 'alpha': specifies the value to use for minimal cost-complexity pruning for regression trees.
`ForestTrainOptions`	`setAttr(Casinvardesc[] value)`
`ForestTrainOptions`	`setAttribute(Casinvardesc[] value)`
`ForestTrainOptions`	`setAttributes(Casinvardesc[] value)` Sets the value of parameter 'attributes': specifies temporary attributes, such as a format, to apply to input variables.
`ForestTrainOptions`	`setAttrs(Casinvardesc[] value)`
`ForestTrainOptions`	`setBinOrder(java.lang.Boolean value)` Sets the value of parameter 'binOrder': by default, the bin order is preserved for numeric variables.
`ForestTrainOptions`	`setBootstrap(java.lang.Double value)` Sets the value of parameter 'bootstrap': specifies the fraction of the data for the bootstrap sample.
`ForestTrainOptions`	`setCasOut(Casouttable value)` Sets the value of parameter 'casOut': specifies the table to store the decision tree model in.
`ForestTrainOptions`	`setCfLev(java.lang.Double value)` Sets the value of parameter 'cfLev': specifies the aggressiveness of tree pruning according to the C4.5 algorithm.
`ForestTrainOptions`	`setCode(Codegen value)` Sets the value of parameter 'code': requests that the action produce SAS score code.
`ForestTrainOptions`	`setCrit(ForestTrainOptions.CRIT value)` Sets the value of parameter 'crit' for alternative 1.
`ForestTrainOptions`	`setCrit(java.lang.Long value)` Sets the value of parameter 'crit' for alternative 2.
`ForestTrainOptions`	`setEvent(java.lang.String[] value)` Sets the value of parameter 'event': specifies the event values of the target variable.
`ForestTrainOptions`	`setEventFreq(java.lang.Double[] value)` Sets the value of parameter 'eventFreq': specifies the frequency for each corresponding event in the event parameter.
`ForestTrainOptions`	`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.
`ForestTrainOptions`	`setIncludeMissing(java.lang.Boolean value)` Sets the value of parameter 'includeMissing': by default, observations with missing values are included.
`ForestTrainOptions`	`setInput(Casinvardesc[] value)`
`ForestTrainOptions`	`setInputs(Casinvardesc[] value)` Sets the value of parameter 'inputs': specifies the input variables to use in the analysis.
`ForestTrainOptions`	`setLeafSize(java.lang.Integer value)` Sets the value of parameter 'leafSize': specifies the minimum number of observations on each node.
`ForestTrainOptions`	`setLoh(java.lang.Integer value)` Sets the value of parameter 'loh': specifies number of variables to split with using the LOH method.
`ForestTrainOptions`	`setM(java.lang.Integer value)` Sets the value of parameter 'm': specifies the number of input variables to consider for splitting on a node.
`ForestTrainOptions`	`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.
`ForestTrainOptions`	`setMaxLevel(java.lang.Integer value)` Sets the value of parameter 'maxLevel': specifies the maximum number of the tree level.
`ForestTrainOptions`	`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.
`ForestTrainOptions`	`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.
`ForestTrainOptions`	`setMissing(ForestTrainOptions.MISSING value)` Sets the value of parameter 'missing': specifies the missing policy to handle missing values.
`ForestTrainOptions`	`setModelId(java.lang.String value)` Sets the value of parameter 'modelId': specifies the model ID variable name to use when generating SAS score code.
`ForestTrainOptions`	`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.
`ForestTrainOptions`	`setNBinsTarget(java.lang.Integer value)` Sets the value of parameter 'nBinsTarget': specifies the number of bins to use for a numerical target variable.
`ForestTrainOptions`	`setNominal(Casinvardesc[] value)`
`ForestTrainOptions`	`setNominals(Casinvardesc[] value)` Sets the value of parameter 'nominals': specifies the nominal input variables to use in the analysis.
`ForestTrainOptions`	`setNTree(java.lang.Integer value)` Sets the value of parameter 'nTree': specifies the number of trees to create.
`ForestTrainOptions`	`setOob(java.lang.Boolean value)` Sets the value of parameter 'oob': when set to True, specifies that the out-of-bag error is computed when building a forest.
`ForestTrainOptions`	`setPrune(java.lang.Boolean value)` Sets the value of parameter 'prune': specify true to use a C4.5 pruning method for classification trees or minimal cost-complexity pruning for regression trees.
`ForestTrainOptions`	`setRbaImp(java.lang.Boolean value)` Sets the value of parameter 'rbaImp': calculate variable importance using the random branch assignments (RBA) method.
`ForestTrainOptions`	`setSeed(java.lang.Double value)` Sets the value of parameter 'seed': specifies the seed for the random number generator.
`ForestTrainOptions`	`setTable(Castable value)` Sets the value of parameter 'table': specifies the settings for an input table.
`ForestTrainOptions`	`setTarget(java.lang.String value)` Sets the value of parameter 'target': specifies the target or response variable for training the decision tree.
`ForestTrainOptions`	`setVarAttrs(Casinvardesc[] value)`
`ForestTrainOptions`	`setVarImp(java.lang.Boolean value)` Sets the value of parameter 'varImp': specifies whether the variable importance information is generated.
`ForestTrainOptions`	`setVote(ForestTrainOptions.VOTE value)` Sets the value of parameter 'vote': specifies the vote strategy for classification.
`ForestTrainOptions`	`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
```
    See Also:
    
    Constant Field Values
  - ACTION_NAME
```
public static final java.lang.String ACTION_NAME
```
    See Also:
    
    Constant Field Values
  - KEY_TABLE
```
public static final java.lang.String KEY_TABLE
```
    See Also:
    
    Constant Field Values
  - KEY_TARGET
```
public static final java.lang.String KEY_TARGET
```
    See Also:
    
    Constant Field Values
  - KEY_INPUTS
```
public static final java.lang.String KEY_INPUTS
```
    See Also:
    
    Constant Field Values
  - KEY_NOMINALS
```
public static final java.lang.String KEY_NOMINALS
```
    See Also:
    
    Constant Field Values
  - KEY_ATTRIBUTES
```
public static final java.lang.String KEY_ATTRIBUTES
```
    See Also:
    
    Constant Field Values
  - KEY_WEIGHT
```
public static final java.lang.String KEY_WEIGHT
```
    See Also:
    
    Constant Field Values
  - KEY_NBINS
```
public static final java.lang.String KEY_NBINS
```
    See Also:
    
    Constant Field Values
  - KEY_NBINSTARGET
```
public static final java.lang.String KEY_NBINSTARGET
```
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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
```
    See Also:
    
    Constant Field Values
  - KEY_LEAFSIZE
```
public static final java.lang.String KEY_LEAFSIZE
```
    See Also:
    
    Constant Field Values
  - KEY_CRIT
```
public static final java.lang.String KEY_CRIT
```
    See Also:
    
    Constant Field Values
  - KEY_MISSING
```
public static final java.lang.String KEY_MISSING
```
    See Also:
    
    Constant Field Values
  - KEY_VOTE
```
public static final java.lang.String KEY_VOTE
```
    See Also:
    
    Constant Field Values
  - KEY_MINUSEINSEARCH
```
public static final java.lang.String KEY_MINUSEINSEARCH
```
    See Also:
    
    Constant Field Values
  - KEY_CFLEV
```
public static final java.lang.String KEY_CFLEV
```
    See Also:
    
    Constant Field Values
  - KEY_ALPHA
```
public static final java.lang.String KEY_ALPHA
```
    See Also:
    
    Constant Field Values
  - KEY_PRUNE
```
public static final java.lang.String KEY_PRUNE
```
    See Also:
    
    Constant Field Values
  - KEY_GREEDY
```
public static final java.lang.String KEY_GREEDY
```
    See Also:
    
    Constant Field Values
  - KEY_BINORDER
```
public static final java.lang.String KEY_BINORDER
```
    See Also:
    
    Constant Field Values
  - KEY_LOH
```
public static final java.lang.String KEY_LOH
```
    See Also:
    
    Constant Field Values
  - KEY_VARIMP
```
public static final java.lang.String KEY_VARIMP
```
    See Also:
    
    Constant Field Values
  - KEY_RBAIMP
```
public static final java.lang.String KEY_RBAIMP
```
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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
```
    See Also:
    
    Constant Field Values
  - KEY_MERGEBIN
```
public static final java.lang.String KEY_MERGEBIN
```
    See Also:
    
    Constant Field Values
  - KEY_INCLUDEMISSING
```
public static final java.lang.String KEY_INCLUDEMISSING
```
    See Also:
    
    Constant Field Values
  - KEY_NTREE
```
public static final java.lang.String KEY_NTREE
```
    See Also:
    
    Constant Field Values
  - KEY_SEED
```
public static final java.lang.String KEY_SEED
```
    See Also:
    
    Constant Field Values
  - KEY_M
```
public static final java.lang.String KEY_M
```
    See Also:
    
    Constant Field Values
  - KEY_BOOTSTRAP
```
public static final java.lang.String KEY_BOOTSTRAP
```
    See Also:
    
    Constant Field Values
  - KEY_OOB
```
public static final java.lang.String KEY_OOB
```
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    Constant Field Values
  - KEY_EVENT
```
public static final java.lang.String KEY_EVENT
```
    See Also:
    
    Constant Field Values
  - KEY_EVENTFREQ
```
public static final java.lang.String KEY_EVENTFREQ
```
    See Also:
    
    Constant Field Values
- Constructor Detail
  - ForestTrainOptions
```
public ForestTrainOptions()
```
  - ForestTrainOptions
```
public ForestTrainOptions(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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions setInput(Casinvardesc[] value)
```
  - getNominals
```
public Casinvardesc[] getNominals()
```
  - getNominal
```
public Casinvardesc[] getNominal()
```
  - setNominals
```
public ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions setAttribute(Casinvardesc[] value)
```
  - setAttrs
```
public ForestTrainOptions setAttrs(Casinvardesc[] value)
```
  - setAttr
```
public ForestTrainOptions setAttr(Casinvardesc[] value)
```
  - setVarAttrs
```
public ForestTrainOptions setVarAttrs(Casinvardesc[] value)
```
  - getWeight
```
public java.lang.String getWeight()
```
  - setWeight
```
public ForestTrainOptions 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
  - getNBins
```
public java.lang.Integer getNBins()
```
  - setNBins
```
public ForestTrainOptions 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
  - getNBinsTarget
```
public java.lang.Integer getNBinsTarget()
```
  - setNBinsTarget
```
public ForestTrainOptions setNBinsTarget(java.lang.Integer value)
```
    Sets the value of parameter 'nBinsTarget': specifies the number of bins to use for a numerical target variable. The server default is 0.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getMaxLevel
```
public java.lang.Integer getMaxLevel()
```
  - setMaxLevel
```
public ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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
  - getCrit
```
public java.lang.Object getCrit()
```
  - setCrit
```
public ForestTrainOptions setCrit(ForestTrainOptions.CRIT value)
```
    Sets the value of parameter 'crit' for alternative 1. The server default is CRIT.GAINRATIO.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - setCrit
```
public ForestTrainOptions setCrit(java.lang.Long value)
```
    Sets the value of parameter 'crit' for alternative 2.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getMissing
```
public ForestTrainOptions.MISSING getMissing()
```
  - setMissing
```
public ForestTrainOptions setMissing(ForestTrainOptions.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
  - getVote
```
public ForestTrainOptions.VOTE getVote()
```
  - setVote
```
public ForestTrainOptions setVote(ForestTrainOptions.VOTE value)
```
    Sets the value of parameter 'vote': specifies the vote strategy for classification. The specified value influences the generated SAS scoring code and the OOB error computations. The server default is VOTE.MAJORITY.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getMinUseInSearch
```
public java.lang.Integer getMinUseInSearch()
```
  - setMinUseInSearch
```
public ForestTrainOptions 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
  - getCfLev
```
public java.lang.Double getCfLev()
```
  - setCfLev
```
public ForestTrainOptions setCfLev(java.lang.Double value)
```
    Sets the value of parameter 'cfLev': specifies the aggressiveness of tree pruning according to the C4.5 algorithm. The server default is 0.25.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getAlpha
```
public java.lang.Double getAlpha()
```
  - setAlpha
```
public ForestTrainOptions setAlpha(java.lang.Double value)
```
    Sets the value of parameter 'alpha': specifies the value to use for minimal cost-complexity pruning for regression trees.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getPrune
```
public java.lang.Boolean getPrune()
```
  - setPrune
```
public ForestTrainOptions setPrune(java.lang.Boolean value)
```
    Sets the value of parameter 'prune': specify true to use a C4.5 pruning method for classification trees or minimal cost-complexity pruning for regression trees. The server default is FALSE.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getGreedy
```
public java.lang.Boolean getGreedy()
```
  - setGreedy
```
public ForestTrainOptions 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 ForestTrainOptions 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
  - getLoh
```
public java.lang.Integer getLoh()
```
  - setLoh
```
public ForestTrainOptions setLoh(java.lang.Integer value)
```
    Sets the value of parameter 'loh': specifies number of variables to split with using the LOH method. The server default is 0.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getVarImp
```
public java.lang.Boolean getVarImp()
```
  - setVarImp
```
public ForestTrainOptions 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
  - getRbaImp
```
public java.lang.Boolean getRbaImp()
```
  - setRbaImp
```
public ForestTrainOptions setRbaImp(java.lang.Boolean value)
```
    Sets the value of parameter 'rbaImp': calculate variable importance using the random branch assignments (RBA) method. The server default is FALSE.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getCode
```
public Codegen getCode()
```
  - setCode
```
public ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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 ForestTrainOptions 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
  - getM
```
public java.lang.Integer getM()
```
  - setM
```
public ForestTrainOptions 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
  - getBootstrap
```
public java.lang.Double getBootstrap()
```
  - setBootstrap
```
public ForestTrainOptions setBootstrap(java.lang.Double value)
```
    Sets the value of parameter 'bootstrap': specifies the fraction of the data for the bootstrap sample. The server default is 0.63212055882.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getOob
```
public java.lang.Boolean getOob()
```
  - setOob
```
public ForestTrainOptions setOob(java.lang.Boolean value)
```
    Sets the value of parameter 'oob': when set to True, specifies that the out-of-bag error is computed when building a forest. This also generates a result table with the OOB error for each tree. The server default is FALSE.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getEvent
```
public java.lang.String[] getEvent()
```
  - setEvent
```
public ForestTrainOptions setEvent(java.lang.String[] value)
```
    Sets the value of parameter 'event': specifies the event values of the target variable. This parameter is combined with the eventFreq parameter to specify the frequency for each specific event. Observations with the specified event are reweighted with the value from the eventFreq parameter. Specifying this parameter is useful for rare-event sampling.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object
  - getEventFreq
```
public java.lang.Double[] getEventFreq()
```
  - setEventFreq
```
public ForestTrainOptions setEventFreq(java.lang.Double[] value)
```
    Sets the value of parameter 'eventFreq': specifies the frequency for each corresponding event in the event parameter.
    
    Parameters:
    
    value - The value
    
    Returns:
    
    The options object

Class ForestTrainOptions

Nested Class Summary

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

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

Field Summary

Fields inherited from class com.sas.cas.CASActionOptions

Constructor Summary

Method Summary

Methods inherited from class com.sas.cas.CASActionOptions

Methods inherited from class java.lang.Object

Methods inherited from interface java.util.Map

Field Detail

ACTION_SET_NAME

ACTION_NAME

KEY_TABLE

KEY_TARGET

KEY_INPUTS

KEY_NOMINALS

KEY_ATTRIBUTES

KEY_WEIGHT

KEY_NBINS

KEY_NBINSTARGET

KEY_MAXLEVEL

KEY_MAXBRANCH

KEY_LEAFSIZE

KEY_CRIT

KEY_MISSING

KEY_VOTE

KEY_MINUSEINSEARCH

KEY_CFLEV

KEY_ALPHA

KEY_PRUNE

KEY_GREEDY

KEY_BINORDER

KEY_LOH

KEY_VARIMP

KEY_RBAIMP

KEY_CODE

KEY_MODELID

KEY_CASOUT

KEY_MERGEBIN

KEY_INCLUDEMISSING

KEY_NTREE

KEY_SEED

KEY_M

KEY_BOOTSTRAP

KEY_OOB

KEY_EVENT

KEY_EVENTFREQ

Constructor Detail

ForestTrainOptions

ForestTrainOptions

Method Detail

getServerDefaultValue

getTable

setTable

getTarget

setTarget

getInputs

getInput

setInputs

setInput

getNominals

getNominal

setNominals

setNominal

getAttributes

getAttribute

getAttrs

getAttr

getVarAttrs

setAttributes

setAttribute

setAttrs

setAttr

setVarAttrs

getWeight

setWeight

getNBins

setNBins