org.apache.spark.ml.odkl

LinearRegressionModel

class LinearRegressionModel extends LinearModel[LinearRegressionModel]

Linear Supertypes
LinearModel[LinearRegressionModel], HasWeights, LinearModelParams, ModelWithSummary[LinearRegressionModel], MLWritable, DirectPredictionModel[Vector, LinearRegressionModel], HasDirectTransformOption, PredictionModel[Vector, LinearRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[LinearRegressionModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. LinearRegressionModel
  2. LinearModel
  3. HasWeights
  4. LinearModelParams
  5. ModelWithSummary
  6. MLWritable
  7. DirectPredictionModel
  8. HasDirectTransformOption
  9. PredictionModel
  10. PredictorParams
  11. HasPredictionCol
  12. HasFeaturesCol
  13. HasLabelCol
  14. Model
  15. Transformer
  16. PipelineStage
  17. Logging
  18. Params
  19. Serializable
  20. Serializable
  21. Identifiable
  22. AnyRef
  23. Any
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Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

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

    Attributes
    protected
    Definition Classes
    Params

  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. final def clear(param: Param[_]): LinearRegressionModel.this.type

    Definition Classes
    Params

  9. def clone(): AnyRef

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

  10. final val coefficients: Param[Vector]

    Definition Classes
    LinearModel

  11. def copy(summary: ModelSummary, params: ParamMap): LinearRegressionModel

    Definition Classes
    ModelWithSummary

  12. def copy(blocks: Map[Block, DataFrame], params: ParamMap = ParamMap()): LinearRegressionModel

    Definition Classes
    ModelWithSummary

  13. def copy(extra: ParamMap): LinearRegressionModel

    Definition Classes
    ModelWithSummary → Model → Transformer → PipelineStage → Params

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

    Attributes
    protected
    Definition Classes
    Params

  15. def create(): LinearRegressionModel

    Definition Classes
    LinearRegressionModel → ModelWithSummary

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

    Attributes
    protected
    Definition Classes
    Params

  17. def directTransform(data: DataFrame): Option[Column]

    returns

    If possible, try to evaluate prediction directly, overwise revert to chain of transformations.

    Definition Classes
    DirectPredictionModel → HasDirectTransformOption

  18. def disableSaveSummary(): ModelWithSummary[LinearRegressionModel]

    Definition Classes
    ModelWithSummary

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

    Definition Classes
    AnyRef

  20. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  22. def explainParams(): String

    Definition Classes
    Params

  23. final def extractParamMap(): ParamMap

    Definition Classes
    Params

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

    Definition Classes
    Params

  25. final val featuresCol: Param[String]

    Definition Classes
    HasFeaturesCol

  26. def featuresDataType: DataType

    Attributes
    protected
    Definition Classes
    PredictionModel

  27. def finalize(): Unit

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

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

    Definition Classes
    Params

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

    Definition Classes
    AnyRef → Any

  30. def getCoefficients: Vector

    Definition Classes
    LinearModel

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

    Definition Classes
    Params

  32. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol

  33. def getIntercept: Double

    Definition Classes
    LinearModel

  34. final def getLabelCol: String

    Definition Classes
    HasLabelCol

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

    Definition Classes
    Params

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

    Definition Classes
    Params

  37. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

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

    Definition Classes
    Params

  39. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  40. def hasParent: Boolean

    Definition Classes
    Model

  41. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  42. val index: String

    Definition Classes
    HasWeights

  43. def init(coefficients: Vector, sqlContext: SQLContext, features: StructField): LinearModel[LinearRegressionModel]

    Attributes
    protected
    Definition Classes
    LinearModel

  44. final val intercept: DoubleParam

    Definition Classes
    LinearModel

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

    Definition Classes
    Params

  46. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

  47. def isSaveSummaryEnabled: Boolean

    Definition Classes
    ModelWithSummary

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

    Definition Classes
    Params

  49. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  50. final val labelCol: Param[String]

    Definition Classes
    HasLabelCol

  51. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  58. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  63. val name: String

    Definition Classes
    HasWeights

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

    Definition Classes
    AnyRef

  65. final def notify(): Unit

    Definition Classes
    AnyRef

  66. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  67. def numFeatures: Int

    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )

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

    Definition Classes
    Params

  69. var parent: Estimator[LinearRegressionModel]

    Definition Classes
    Model

  70. def postProcess(value: Double): Double

    Definition Classes
    LinearRegressionModel → LinearModel

  71. final def predict(features: Vector): Double

    Attributes
    protected
    Definition Classes
    LinearModel → DirectPredictionModel → PredictionModel

  72. def predictDirect(features: Any): Double

    Definition Classes
    DirectPredictionModel

  73. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  74. def save(path: String): Unit

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

  75. final def set(paramPair: ParamPair[_]): LinearRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  76. final def set(param: String, value: Any): LinearRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    Params

  78. final def setDefault(paramPairs: ParamPair[_]*): LinearRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

  80. def setFeaturesCol(value: String): LinearRegressionModel

    Definition Classes
    PredictionModel

  81. def setParent(parent: Estimator[LinearRegressionModel]): LinearRegressionModel

    Definition Classes
    Model

  82. def setPredictionCol(value: String): LinearRegressionModel

    Definition Classes
    PredictionModel

  83. def summary: ModelSummary

    Definition Classes
    ModelWithSummary

  84. val summaryParam: Param[ModelSummary]

    Attributes
    protected
    Definition Classes
    ModelWithSummary

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

    Definition Classes
    AnyRef

  86. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  87. def transform(dataset: DataFrame): DataFrame

    Definition Classes
    PredictionModel → Transformer

  88. def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame

    Definition Classes
    Transformer

  89. def transform(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    Definition Classes
    Transformer
    Annotations
    @varargs()

  90. def transformImpl(dataset: DataFrame): DataFrame

    Attributes
    protected
    Definition Classes
    PredictionModel

  91. def transformSchema(schema: StructType): StructType

    Definition Classes
    PredictionModel → PipelineStage

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

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

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

    Attributes
    protected
    Definition Classes
    PredictorParams

  94. def validateParams(): Unit

    Definition Classes
    Params

  95. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  98. val weight: String

    Definition Classes
    HasWeights

  99. val weights: Block

    Definition Classes
    HasWeights

  100. def write: WithSummaryWriter[LinearRegressionModel]

    Definition Classes
    ModelWithSummary → MLWritable

Inherited from LinearModel[LinearRegressionModel]

Inherited from HasWeights

Inherited from LinearModelParams

Inherited from ModelWithSummary[LinearRegressionModel]

Inherited from MLWritable

Inherited from DirectPredictionModel[Vector, LinearRegressionModel]

Inherited from HasDirectTransformOption

Inherited from PredictionModel[Vector, LinearRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[LinearRegressionModel]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped