Packages

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

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
SynapseMLLogging, AutoTrainer[TrainedClassifierModel], Wrappable, RWrappable, PythonWrappable, BaseWrappable, HasFeaturesCol, ComplexParamsWritable, MLWritable, HasInputCols, HasLabelCol, Estimator[TrainedClassifierModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainClassifier
  2. SynapseMLLogging
  3. AutoTrainer
  4. Wrappable
  5. RWrappable
  6. PythonWrappable
  7. BaseWrappable
  8. HasFeaturesCol
  9. ComplexParamsWritable
  10. MLWritable
  11. HasInputCols
  12. HasLabelCol
  13. Estimator
  14. PipelineStage
  15. Logging
  16. Params
  17. Serializable
  18. Serializable
  19. Identifiable
  20. AnyRef
  21. 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 getInputCols: Array[String]

    Definition Classes
    HasInputCols
  33. def getLabelCol: String

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

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

    Definition Classes
    AutoTrainer
  36. def getNumFeatures: Int

    Definition Classes
    AutoTrainer
  37. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  38. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  39. def getParamInfo(p: Param[_]): ParamInfo[_]
    Definition Classes
    BaseWrappable
  40. def getPayload(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], exception: Option[Exception]): Map[String, String]
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  41. def getReindexLabel: Boolean

  42. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  43. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  44. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  45. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  46. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  47. val inputCols: StringArrayParam

    The names of the inputColumns

    The names of the inputColumns

    Definition Classes
    HasInputCols
  48. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  49. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  50. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  51. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  52. val labelCol: Param[String]

    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol
  53. 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.

  54. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  55. def logBase(info: Map[String, String], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  56. def logBase(methodName: String, numCols: Option[Int], executionSeconds: Option[Double], featureName: Option[String]): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  57. def logClass(featureName: String): Unit
    Definition Classes
    SynapseMLLogging
  58. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  59. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  60. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  61. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  62. def logErrorBase(methodName: String, e: Exception): Unit
    Attributes
    protected
    Definition Classes
    SynapseMLLogging
  63. def logFit[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  64. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  67. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logTransform[T](f: ⇒ T, columns: Int): T
    Definition Classes
    SynapseMLLogging
  70. def logVerb[T](verb: String, f: ⇒ T, columns: Option[Int] = None): T
    Definition Classes
    SynapseMLLogging
  71. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def makePyFile(conf: CodegenConfig): Unit
    Definition Classes
    PythonWrappable
  74. def makeRFile(conf: CodegenConfig): Unit
    Definition Classes
    RWrappable
  75. val model: EstimatorParam

    Model to run.

    Model to run. See doc on derived classes.

    Definition Classes
    AutoTrainer
  76. def modelDoc: String

    Doc for model to run.

    Doc for model to run.

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

    Number of features to hash to

    Number of features to hash to

    Definition Classes
    AutoTrainer
  81. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  82. def pyAdditionalMethods: String
    Definition Classes
    PythonWrappable
  83. lazy val pyClassDoc: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  84. lazy val pyClassName: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  85. def pyExtraEstimatorImports: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  86. def pyExtraEstimatorMethods: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  87. lazy val pyInheritedClasses: Seq[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  88. def pyInitFunc(): String
    Definition Classes
    PythonWrappable
  89. lazy val pyInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    PythonWrappable
  90. lazy val pyObjectBaseClass: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  91. def pyParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  92. def pyParamDefault[T](p: Param[T]): Option[String]
    Attributes
    protected
    Definition Classes
    PythonWrappable
  93. def pyParamGetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  94. def pyParamSetter(p: Param[_]): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  95. def pyParamsArgs: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  96. def pyParamsDefaults: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  97. lazy val pyParamsDefinitions: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  98. def pyParamsGetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  99. def pyParamsSetters: String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  100. def pythonClass(): String
    Attributes
    protected
    Definition Classes
    PythonWrappable
  101. def rClass(): String
    Attributes
    protected
    Definition Classes
    RWrappable
  102. def rDocString: String
    Attributes
    protected
    Definition Classes
    RWrappable
  103. def rExtraBodyLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  104. def rExtraInitLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  105. lazy val rFuncName: String
    Attributes
    protected
    Definition Classes
    RWrappable
  106. lazy val rInternalWrapper: Boolean
    Attributes
    protected
    Definition Classes
    RWrappable
  107. def rParamArg[T](p: Param[T]): String
    Attributes
    protected
    Definition Classes
    RWrappable
  108. def rParamsArgs: String
    Attributes
    protected
    Definition Classes
    RWrappable
  109. def rSetterLines: String
    Attributes
    protected
    Definition Classes
    RWrappable
  110. 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.

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

    Definition Classes
    HasFeaturesCol
  118. def setInputCols(value: Array[String]): TrainClassifier.this.type

    Definition Classes
    HasInputCols
  119. def setLabelCol(value: String): TrainClassifier.this.type

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

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

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

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

  124. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  125. val thisStage: Params
    Attributes
    protected
    Definition Classes
    BaseWrappable
  126. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  127. def transformSchema(schema: StructType): StructType
    Definition Classes
    TrainClassifier → PipelineStage
    Annotations
    @DeveloperApi()
  128. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  129. val uid: String
    Definition Classes
    TrainClassifier → SynapseMLLogging → Identifiable
  130. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  131. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  132. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  133. def write: MLWriter
    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from SynapseMLLogging

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 HasInputCols

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