org.apache.spark.ml.odkl

LogisticRegressionModel

class LogisticRegressionModel extends LinearModel[LogisticRegressionModel]

Linear Supertypes
LinearModel[LogisticRegressionModel], HasWeights, LinearModelParams, ModelWithSummary[LogisticRegressionModel], MLWritable, DirectPredictionModel[Vector, LogisticRegressionModel], HasDirectTransformOption, PredictionModel[Vector, LogisticRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Model[LogisticRegressionModel], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. LogisticRegressionModel
  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[_]): LogisticRegressionModel.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): LogisticRegressionModel

    Definition Classes
    ModelWithSummary
  12. def copy(blocks: Map[Block, DataFrame], params: ParamMap = ParamMap()): LogisticRegressionModel

    Definition Classes
    ModelWithSummary
  13. def copy(extra: ParamMap): LogisticRegressionModel

    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(): LogisticRegressionModel

  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
    DirectPredictionModelHasDirectTransformOption
  18. def disableSaveSummary(): ModelWithSummary[LogisticRegressionModel]

    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[LogisticRegressionModel]

    Attributes
    protected
    Definition Classes
    LinearModel
  44. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    Attributes
    protected
    Definition Classes
    Logging
  45. final val intercept: DoubleParam

    Definition Classes
    LinearModel
  46. final def isDefined(param: Param[_]): Boolean

    Definition Classes
    Params
  47. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  48. def isSaveSummaryEnabled: Boolean

    Definition Classes
    ModelWithSummary
  49. final def isSet(param: Param[_]): Boolean

    Definition Classes
    Params
  50. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging
  51. final val labelCol: Param[String]

    Definition Classes
    HasLabelCol
  52. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging
  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 logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  58. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  59. def logName: String

    Attributes
    protected
    Definition Classes
    Logging
  60. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  61. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  62. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging
  63. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging
  64. val name: String

    Definition Classes
    HasWeights
  65. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  66. final def notify(): Unit

    Definition Classes
    AnyRef
  67. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  68. def numFeatures: Int

    Definition Classes
    PredictionModel
    Annotations
    @Since( "1.6.0" )
  69. lazy val params: Array[Param[_]]

    Definition Classes
    Params
  70. var parent: Estimator[LogisticRegressionModel]

    Definition Classes
    Model
  71. def postProcess(value: Double): Double

    Definition Classes
    LogisticRegressionModelLinearModel
  72. final def predict(features: Vector): Double

    Attributes
    protected
    Definition Classes
    LinearModelDirectPredictionModel → PredictionModel
  73. def predictDirect(features: Any): Double

    Definition Classes
    DirectPredictionModel
  74. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol
  75. def save(path: String): Unit

    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  76. final def set(paramPair: ParamPair[_]): LogisticRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params
  77. final def set(param: String, value: Any): LogisticRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params
  78. final def set[T](param: Param[T], value: T): LogisticRegressionModel.this.type

    Definition Classes
    Params
  79. final def setDefault(paramPairs: ParamPair[_]*): LogisticRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params
  80. final def setDefault[T](param: Param[T], value: T): LogisticRegressionModel.this.type

    Attributes
    protected
    Definition Classes
    Params
  81. def setFeaturesCol(value: String): LogisticRegressionModel

    Definition Classes
    PredictionModel
  82. def setParent(parent: Estimator[LogisticRegressionModel]): LogisticRegressionModel

    Definition Classes
    Model
  83. def setPredictionCol(value: String): LogisticRegressionModel

    Definition Classes
    PredictionModel
  84. def summary: ModelSummary

    Definition Classes
    ModelWithSummary
  85. val summaryParam: Param[ModelSummary]

    Attributes
    protected
    Definition Classes
    ModelWithSummary
  86. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  87. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any
  88. def transform(dataset: Dataset[_]): DataFrame

    Definition Classes
    PredictionModel → Transformer
  89. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  90. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  91. def transformImpl(dataset: Dataset[_]): DataFrame

    Attributes
    protected
    Definition Classes
    PredictionModel
  92. def transformSchema(schema: StructType): StructType

    Definition Classes
    PredictionModel → PipelineStage
  93. def transformSchema(schema: StructType, logging: Boolean): StructType

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  94. def validateAndTransformSchema(schema: StructType, fitting: Boolean, featuresDataType: DataType): StructType

    Attributes
    protected
    Definition Classes
    PredictorParams
  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[LogisticRegressionModel]

    Definition Classes
    ModelWithSummary → MLWritable

Inherited from HasWeights

Inherited from LinearModelParams

Inherited from MLWritable

Inherited from HasDirectTransformOption

Inherited from PredictionModel[Vector, LogisticRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Model[LogisticRegressionModel]

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