Packages

class TrainClassifier extends Estimator[TrainedClassifierModel] with AutoTrainer[TrainedClassifierModel] with BasicLogging

Trains a classification model. Featurizes the given data into a vector of doubles.

Note the behavior of the reindex and labels parameters, the parameters interact as:

reindex -> false labels -> false (Empty) Assume all double values, don't use metadata, assume natural ordering

reindex -> true labels -> false (Empty) Index, use natural ordering of string indexer

reindex -> false labels -> true (Specified) Assume user knows indexing, apply label values. Currently only string type supported.

reindex -> true labels -> true (Specified) Validate labels matches column type, try to recast to label type, reindex label column

The currently supported classifiers are: Logistic Regression Classifier Decision Tree Classifier Random Forest Classifier Gradient Boosted Trees Classifier Naive Bayes Classifier Multilayer Perceptron Classifier In addition to any generic learner that inherits from Predictor.

Linear Supertypes
BasicLogging, AutoTrainer[TrainedClassifierModel], Wrappable, RWrappable, PythonWrappable, BaseWrappable, HasFeaturesCol, ComplexParamsWritable, MLWritable, HasLabelCol, Estimator[TrainedClassifierModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainClassifier
  2. BasicLogging
  3. AutoTrainer
  4. Wrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. HasFeaturesCol
  9. ComplexParamsWritable
  10. MLWritable
  11. HasLabelCol
  12. Estimator
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Serializable
  18. Identifiable
  19. AnyRef
  20. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TrainClassifier()
  2. new TrainClassifier(uid: String)

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. lazy val classNameHelper: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  7. final def clear(param: Param[_]): TrainClassifier.this.type
    Definition Classes
    Params
  8. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  9. def companionModelClassName: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  10. def convertLabel(dataset: Dataset[_], labelColumn: String, labelValues: Option[Array[_]]): (DataFrame, Option[Array[_]])
  11. def copy(extra: ParamMap): Estimator[TrainedClassifierModel]
    Definition Classes
    TrainClassifier → Estimator → PipelineStage → Params
  12. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  13. lazy val copyrightLines: String
    Attributes
    protected
    Definition Classes
    BaseWrappable
  14. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  15. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  16. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  17. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  18. def explainParams(): String
    Definition Classes
    Params
  19. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  20. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  21. val featuresCol: Param[String]

    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol
  22. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  23. def fit(dataset: Dataset[_]): TrainedClassifierModel

    Fits the classification model.

    Fits the classification model.

    dataset

    The input dataset to train.

    returns

    The trained classification model.

    Definition Classes
    TrainClassifier → Estimator
  24. def fit(dataset: Dataset[_], paramMaps: Seq[ParamMap]): Seq[TrainedClassifierModel]
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  25. def fit(dataset: Dataset[_], paramMap: ParamMap): TrainedClassifierModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )
  26. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedClassifierModel
    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  27. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  28. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  29. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  30. def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol
  31. def getFeaturizeParams: (Boolean, Boolean, Int)
  32. def getLabelCol: String

    Definition Classes
    HasLabelCol
  33. def getLabels: Array[String]

  34. def getModel: Estimator[_ <: Model[_]]

    Definition Classes
    AutoTrainer
  35. def getNumFeatures: Int

    Definition Classes
    AutoTrainer
  36. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  37. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  38. def getReindexLabel: Boolean

  39. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  40. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  41. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  42. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  43. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  44. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  45. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  46. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  47. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  48. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  49. val labels: StringArrayParam

    Specifies the labels metadata on the column.

    Specifies the labels metadata on the column. See class documentation for how this parameter interacts with reindex labels parameter.

  50. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  51. def logBase(methodName: String): Unit
    Attributes
    protected
    Definition Classes
    BasicLogging
  52. def logClass(): Unit
    Definition Classes
    BasicLogging
  53. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  54. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  55. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  56. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  57. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    BasicLogging
  58. def logFit[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  59. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  62. def logPredict[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  63. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  64. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logTrain[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  66. def logTransform[T](f: ⇒ T): T
    Definition Classes
    BasicLogging
  67. def logVerb[T](verb: String, f: ⇒ T): T
    Definition Classes
    BasicLogging
  68. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  71. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  72. val model: EstimatorParam

    Model to run.

    Model to run. See doc on derived classes.

    Definition Classes
    AutoTrainer
  73. def modelDoc: String

    Doc for model to run.

    Doc for model to run.

    Definition Classes
    TrainClassifier → AutoTrainer
  74. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  75. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  76. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  77. val numFeatures: IntParam

    Number of features to hash to

    Number of features to hash to

    Definition Classes
    AutoTrainer
  78. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  79. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  80. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  81. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  82. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  83. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  84. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  85. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  86. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    PythonWrappable
  87. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  88. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  89. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  90. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  91. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  92. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  93. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  94. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  95. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  96. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  97. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  98. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  99. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  100. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  101. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  102. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  103. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  104. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  105. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  106. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  107. val reindexLabel: BooleanParam

    Specifies whether to reindex the given label column.

    Specifies whether to reindex the given label column. See class documentation for how this parameter interacts with specified labels.

  108. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  109. final def set(paramPair: ParamPair[_]): TrainClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  110. final def set(param: String, value: Any): TrainClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  111. final def set[T](param: Param[T], value: T): TrainClassifier.this.type
    Definition Classes
    Params
  112. final def setDefault(paramPairs: ParamPair[_]*): TrainClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  113. final def setDefault[T](param: Param[T], value: T): TrainClassifier.this.type
    Attributes
    protected
    Definition Classes
    Params
  114. def setFeaturesCol(value: String): TrainClassifier.this.type

    Definition Classes
    HasFeaturesCol
  115. def setLabelCol(value: String): TrainClassifier.this.type

    Definition Classes
    HasLabelCol
  116. def setLabels(value: Array[String]): TrainClassifier.this.type

  117. def setModel(value: Estimator[_ <: Model[_]]): TrainClassifier.this.type

    Definition Classes
    AutoTrainer
  118. def setNumFeatures(value: Int): TrainClassifier.this.type

    Definition Classes
    AutoTrainer
  119. def setReindexLabel(value: Boolean): TrainClassifier.this.type

  120. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  121. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  122. def transformSchema(schema: StructType): StructType
    Definition Classes
    TrainClassifier → PipelineStage
    Annotations
    @DeveloperApi()
  123. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  124. val uid: String
    Definition Classes
    TrainClassifier → BasicLogging → Identifiable
  125. val ver: String
    Definition Classes
    BasicLogging
  126. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  127. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  128. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  129. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from BasicLogging

Inherited from AutoTrainer[TrainedClassifierModel]

Inherited from Wrappable

Inherited from RWrappable

Inherited from PythonWrappable

Inherited from BaseWrappable

Inherited from HasFeaturesCol

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from HasLabelCol

Inherited from Estimator[TrainedClassifierModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

getParam

param

setParam

Ungrouped