Class/Object

com.microsoft.ml.spark.train

TrainClassifier

Related Docs: object TrainClassifier | package train

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

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.

Annotations
@InternalWrapper()
Linear Supertypes
AutoTrainer[TrainedClassifierModel], HasFeaturesCol, ComplexParamsWritable, MLWritable, HasLabelCol, Wrappable, Estimator[TrainedClassifierModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. TrainClassifier
  2. AutoTrainer
  3. HasFeaturesCol
  4. ComplexParamsWritable
  5. MLWritable
  6. HasLabelCol
  7. Wrappable
  8. Estimator
  9. PipelineStage
  10. Logging
  11. Params
  12. Serializable
  13. Serializable
  14. Identifiable
  15. AnyRef
  16. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new TrainClassifier()

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  2. new TrainClassifier(uid: String)

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Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any

  3. final def $[T](param: Param[T]): T

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    Attributes
    protected
    Definition Classes
    Params

  4. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  5. def additionalPythonMethods(): String

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    Definition Classes
    Wrappable

  6. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  7. final def clear(param: Param[_]): TrainClassifier.this.type

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    Definition Classes
    Params

  8. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  9. def convertLabel(dataset: Dataset[_], labelColumn: String, labelValues: Option[Array[_]]): (DataFrame, Option[Array[_]])

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  10. def copy(extra: ParamMap): Estimator[TrainedClassifierModel]

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    Definition Classes
    TrainClassifier → Estimator → PipelineStage → Params

  11. def copyValues[T <: Params](to: T, extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params

  12. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params

  13. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  14. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any

  15. def explainParam(param: Param[_]): String

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    Definition Classes
    Params

  16. def explainParams(): String

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    Definition Classes
    Params

  17. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

  18. final def extractParamMap(extra: ParamMap): ParamMap

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    Definition Classes
    Params

  19. val featuresCol: Param[String]

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    The name of the features column

    The name of the features column

    Definition Classes
    HasFeaturesCol

  20. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

  21. def fit(dataset: Dataset[_]): TrainedClassifierModel

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    Fits the classification model.

    Fits the classification model.

    dataset

    The input dataset to train.

    returns

    The trained classification model.

    Definition Classes
    TrainClassifier → Estimator

  22. def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[TrainedClassifierModel]

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  23. def fit(dataset: Dataset[_], paramMap: ParamMap): TrainedClassifierModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  24. def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): TrainedClassifierModel

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()

  25. final def get[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  26. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any

  27. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params

  28. def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  29. def getFeaturizeParams: (Boolean, Boolean, Int)

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  30. def getLabelCol: String

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    Definition Classes
    HasLabelCol

  31. def getLabels: Array[String]

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

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    Definition Classes
    AutoTrainer

  33. def getNumFeatures: Int

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    Definition Classes
    AutoTrainer

  34. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params

  35. def getParam(paramName: String): Param[Any]

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    Definition Classes
    Params

  36. def getReindexLabel: Boolean

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  37. final def hasDefault[T](param: Param[T]): Boolean

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    Definition Classes
    Params

  38. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  39. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  40. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  41. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  42. final def isDefined(param: Param[_]): Boolean

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    Definition Classes
    Params

  43. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

  44. final def isSet(param: Param[_]): Boolean

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    Definition Classes
    Params

  45. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  46. val labelCol: Param[String]

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    The name of the label column

    The name of the label column

    Definition Classes
    HasLabelCol

  47. val labels: StringArrayParam

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    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.

  48. def log: Logger

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    Attributes
    protected
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    Logging

  49. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
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    Logging

  50. def logDebug(msg: ⇒ String): Unit

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    protected
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    Logging

  51. def logError(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging

  52. def logError(msg: ⇒ String): Unit

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    protected
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    Logging

  53. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging

  54. def logInfo(msg: ⇒ String): Unit

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    protected
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    Logging

  55. def logName: String

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    protected
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    Logging

  56. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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    protected
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    Logging

  57. def logTrace(msg: ⇒ String): Unit

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    Attributes
    protected
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    Logging

  58. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

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    Attributes
    protected
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    Logging

  59. def logWarning(msg: ⇒ String): Unit

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    Attributes
    protected
    Definition Classes
    Logging

  60. val model: EstimatorParam

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    Model to run.

    Model to run. See doc on derived classes.

    Definition Classes
    AutoTrainer

  61. def modelDoc: String

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    Doc for model to run.

    Doc for model to run.

    Definition Classes
    TrainClassifier → AutoTrainer

  62. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef

  63. final def notify(): Unit

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    Definition Classes
    AnyRef

  64. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

  65. val numFeatures: IntParam

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    Number of features to hash to

    Number of features to hash to

    Definition Classes
    AutoTrainer

  66. lazy val params: Array[Param[_]]

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    Definition Classes
    Params

  67. val reindexLabel: BooleanParam

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    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.

  68. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )

  69. final def set(paramPair: ParamPair[_]): TrainClassifier.this.type

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    Attributes
    protected
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    Params

  70. final def set(param: String, value: Any): TrainClassifier.this.type

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    Attributes
    protected
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    Params

  71. final def set[T](param: Param[T], value: T): TrainClassifier.this.type

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    Definition Classes
    Params

  72. final def setDefault(paramPairs: ParamPair[_]*): TrainClassifier.this.type

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    Attributes
    protected
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    Params

  73. final def setDefault[T](param: Param[T], value: T): TrainClassifier.this.type

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    Attributes
    protected
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    Params

  74. def setFeaturesCol(value: String): TrainClassifier.this.type

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    Definition Classes
    HasFeaturesCol

  75. def setLabelCol(value: String): TrainClassifier.this.type

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    Definition Classes
    HasLabelCol

  76. def setLabels(value: Array[String]): TrainClassifier.this.type

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

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    Definition Classes
    AutoTrainer

  78. def setNumFeatures(value: Int): TrainClassifier.this.type

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    Definition Classes
    AutoTrainer

  79. def setReindexLabel(value: Boolean): TrainClassifier.this.type

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  80. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef

  81. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  82. def transformSchema(schema: StructType): StructType

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    Definition Classes
    TrainClassifier → PipelineStage
    Annotations
    @DeveloperApi()

  83. def transformSchema(schema: StructType, logging: Boolean): StructType

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  84. val uid: String

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    Definition Classes
    TrainClassifier → Identifiable

  85. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  86. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  87. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  88. def write: MLWriter

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    Definition Classes
    ComplexParamsWritable → MLWritable

Inherited from AutoTrainer[TrainedClassifierModel]

Inherited from HasFeaturesCol

Inherited from ComplexParamsWritable

Inherited from MLWritable

Inherited from HasLabelCol

Inherited from Wrappable

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