Class

org.apache.spark.ml.odkl

LinearRegressor

Related Doc: package odkl

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abstract class LinearRegressor[M <: LinearModel[M], O <: Optimizer, T <: LinearRegressor[M, O, T]] extends LinearEstimator[M, T] with DefaultParamsWritable with HasCacheTrainData

Linear Supertypes
HasCacheTrainData, DefaultParamsWritable, MLWritable, LinearEstimator[M, T], HasWeights, LinearModelParams, SummarizableEstimator[M], Predictor[Vector, T, M], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[M], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
LinearRegressionSGD, LogisticRegressionLBFSG
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. LinearRegressor
  2. HasCacheTrainData
  3. DefaultParamsWritable
  4. MLWritable
  5. LinearEstimator
  6. HasWeights
  7. LinearModelParams
  8. SummarizableEstimator
  9. Predictor
  10. PredictorParams
  11. HasPredictionCol
  12. HasFeaturesCol
  13. HasLabelCol
  14. Estimator
  15. PipelineStage
  16. Logging
  17. Params
  18. Serializable
  19. Serializable
  20. Identifiable
  21. AnyRef
  22. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new LinearRegressor(uid: String)

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Abstract Value Members

  1. abstract def createModel(optimizer: O, coefficients: Vector, sqlContext: SQLContext, features: StructField): M

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    Attributes
    protected

  2. abstract def createOptimizer(): O

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    Attributes
    protected

Concrete 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. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any

  6. final val cacheTrainData: BooleanParam

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    Definition Classes
    HasCacheTrainData

  7. final def clear(param: Param[_]): LinearRegressor.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 copy(extra: ParamMap): T

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    Definition Classes
    LinearRegressor → LinearEstimator → SummarizableEstimator → Predictor → Estimator → PipelineStage → Params

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

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    Attributes
    protected
    Definition Classes
    Params

  11. def createWeightsSummary(coefficients: Vector, sqlContext: SQLContext, features: StructField): DataFrame

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    Attributes
    protected

  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. def extractLabeledPoints(dataset: Dataset[_]): RDD[LabeledPoint]

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    Attributes
    protected
    Definition Classes
    Predictor

  18. final def extractParamMap(): ParamMap

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  20. final val featuresCol: Param[String]

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    Definition Classes
    HasFeaturesCol

  21. def finalize(): Unit

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

  22. def fit(dataset: Dataset[_]): M

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    Definition Classes
    Predictor → Estimator

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

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

  24. def fit(dataset: Dataset[_], paramMap: ParamMap): M

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" )

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

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

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

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    Definition Classes
    Params

  27. final def getCacheTrainData: Boolean

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    Definition Classes
    HasCacheTrainData

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

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    Definition Classes
    AnyRef → Any

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

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    Definition Classes
    Params

  30. final def getFeaturesCol: String

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    Definition Classes
    HasFeaturesCol

  31. final def getLabelCol: String

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    Definition Classes
    HasLabelCol

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

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    Definition Classes
    Params

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

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    Definition Classes
    Params

  34. final def getPredictionCol: String

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    Definition Classes
    HasPredictionCol

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

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    Definition Classes
    Params

  36. def hasParam(paramName: String): Boolean

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    Definition Classes
    Params

  37. def hashCode(): Int

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    Definition Classes
    AnyRef → Any

  38. val index: String

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    Definition Classes
    HasWeights

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

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    Attributes
    protected
    Definition Classes
    Logging

  40. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Definition Classes
    Params

  42. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any

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

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    Definition Classes
    Params

  44. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging

  45. final val labelCol: Param[String]

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    Definition Classes
    HasLabelCol

  46. def log: Logger

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  53. def logName: String

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

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

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    Attributes
    protected
    Definition Classes
    Logging

  58. val name: String

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    Definition Classes
    HasWeights

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

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    Definition Classes
    AnyRef

  60. final def notify(): Unit

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    Definition Classes
    AnyRef

  61. final def notifyAll(): Unit

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    Definition Classes
    AnyRef

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

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    Definition Classes
    Params

  63. final val predictionCol: Param[String]

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    Definition Classes
    HasPredictionCol

  64. def save(path: String): Unit

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

  65. final def set(paramPair: ParamPair[_]): LinearRegressor.this.type

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    Attributes
    protected
    Definition Classes
    Params

  66. final def set(param: String, value: Any): LinearRegressor.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Definition Classes
    Params

  68. def setCacheTrainData(value: Boolean): LinearRegressor.this.type

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    Definition Classes
    HasCacheTrainData

  69. final def setDefault(paramPairs: ParamPair[_]*): LinearRegressor.this.type

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    Attributes
    protected
    Definition Classes
    Params

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

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    Attributes
    protected
    Definition Classes
    Params

  71. def setFeaturesCol(value: String): T

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    Definition Classes
    Predictor

  72. def setLabelCol(value: String): T

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    Definition Classes
    Predictor

  73. def setPredictionCol(value: String): T

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    Definition Classes
    Predictor

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

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    Definition Classes
    AnyRef

  75. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any

  76. def train(dataset: Dataset[_]): M

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    Attributes
    protected
    Definition Classes
    LinearRegressor → Predictor

  77. def transformSchema(schema: StructType): StructType

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    Definition Classes
    Predictor → PipelineStage

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

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    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  79. val uid: String

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    Definition Classes
    LinearRegressor → Identifiable

  80. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

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    Attributes
    protected
    Definition Classes
    PredictorParams

  81. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  84. val weight: String

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    Definition Classes
    HasWeights

  85. val weights: Block

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    Definition Classes
    HasWeights

  86. def write: MLWriter

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    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from HasCacheTrainData

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from LinearEstimator[M, T]

Inherited from HasWeights

Inherited from LinearModelParams

Inherited from SummarizableEstimator[M]

Inherited from Predictor[Vector, T, M]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[M]

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

Ungrouped