org.apache.spark.ml.odkl

LogisticRegressionLBFSG

class LogisticRegressionLBFSG extends LinearRegressor[LogisticRegressionModel, LogisticRegressionLBFSG, LogisticRegressionLBFSG] with HasRegParam with HasTol with HasMaxIter with Optimizer with HasElasticNetParam with HasRegularizeLast with HasBatchSize

Linear Supertypes
HasBatchSize, HasRegularizeLast, HasElasticNetParam, Optimizer, HasMaxIter, HasTol, HasRegParam, LinearRegressor[LogisticRegressionModel, LogisticRegressionLBFSG, LogisticRegressionLBFSG], HasCacheTrainData, DefaultParamsWritable, MLWritable, LinearEstimator[LogisticRegressionModel, LogisticRegressionLBFSG], HasWeights, LinearModelParams, SummarizableEstimator[LogisticRegressionModel], Predictor[Vector, LogisticRegressionLBFSG, LogisticRegressionModel], PredictorParams, HasPredictionCol, HasFeaturesCol, HasLabelCol, Estimator[LogisticRegressionModel], PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. LogisticRegressionLBFSG
  2. HasBatchSize
  3. HasRegularizeLast
  4. HasElasticNetParam
  5. Optimizer
  6. HasMaxIter
  7. HasTol
  8. HasRegParam
  9. LinearRegressor
  10. HasCacheTrainData
  11. DefaultParamsWritable
  12. MLWritable
  13. LinearEstimator
  14. HasWeights
  15. LinearModelParams
  16. SummarizableEstimator
  17. Predictor
  18. PredictorParams
  19. HasPredictionCol
  20. HasFeaturesCol
  21. HasLabelCol
  22. Estimator
  23. PipelineStage
  24. Logging
  25. Params
  26. Serializable
  27. Serializable
  28. Identifiable
  29. AnyRef
  30. Any
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Instance Constructors

  1. new LogisticRegressionLBFSG()

  2. new LogisticRegressionLBFSG(uid: String)

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. val batchSize: Param[Int]

    Definition Classes
    HasBatchSize

  9. final val cacheTrainData: BooleanParam

    Definition Classes
    HasCacheTrainData

  10. final def clear(param: Param[_]): LogisticRegressionLBFSG.this.type

    Definition Classes
    Params

  11. def clone(): AnyRef

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

  12. def copy(extra: ParamMap): LogisticRegressionLBFSG

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

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

    Attributes
    protected
    Definition Classes
    Params

  14. def createModel(optimizer: LogisticRegressionLBFSG, coefficients: Vector, sqlContext: SQLContext, features: StructField): LogisticRegressionModel

    Attributes
    protected
    Definition Classes
    LogisticRegressionLBFSG → LinearRegressor

  15. def createOptimizer(): LogisticRegressionLBFSG

    Attributes
    protected
    Definition Classes
    LogisticRegressionLBFSG → LinearRegressor

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

    Attributes
    protected
    Definition Classes
    LinearRegressor

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

    Attributes
    protected
    Definition Classes
    Params

  18. final val elasticNetParam: DoubleParam

    Definition Classes
    HasElasticNetParam

  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. def extractLabeledPoints(dataset: DataFrame): RDD[LabeledPoint]

    Attributes
    protected
    Definition Classes
    Predictor

  24. final def extractParamMap(): ParamMap

    Definition Classes
    Params

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

    Definition Classes
    Params

  26. final val featuresCol: Param[String]

    Definition Classes
    HasFeaturesCol

  27. def finalize(): Unit

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

  28. def fit(dataset: DataFrame): LogisticRegressionModel

    Definition Classes
    Predictor → Estimator

  29. def fit(dataset: DataFrame, paramMaps: Array[ParamMap]): Seq[LogisticRegressionModel]

    Definition Classes
    Estimator

  30. def fit(dataset: DataFrame, paramMap: ParamMap): LogisticRegressionModel

    Definition Classes
    Estimator

  31. def fit(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): LogisticRegressionModel

    Definition Classes
    Estimator
    Annotations
    @varargs()

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

    Definition Classes
    Params

  33. def getBatchSize: Int

    Definition Classes
    HasBatchSize

  34. final def getCacheTrainData: Boolean

    Definition Classes
    HasCacheTrainData

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

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  37. final def getElasticNetParam: Double

    Definition Classes
    HasElasticNetParam

  38. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol

  39. final def getLabelCol: String

    Definition Classes
    HasLabelCol

  40. final def getMaxIter: Int

    Definition Classes
    HasMaxIter

  41. final def getNumCorrections: Int

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

    Definition Classes
    Params

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

    Definition Classes
    Params

  44. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

  45. final def getRegParam: Double

    Definition Classes
    HasRegParam

  46. def getRegularizeLast: Boolean

    Definition Classes
    HasRegularizeLast

  47. final def getTol: Double

    Definition Classes
    HasTol

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

    Definition Classes
    Params

  49. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  50. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  51. val index: String

    Definition Classes
    HasWeights

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

    Definition Classes
    Params

  53. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    Params

  55. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  56. final val labelCol: Param[String]

    Definition Classes
    HasLabelCol

  57. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

  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 logInfo(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  64. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  69. final val maxIter: IntParam

    Definition Classes
    HasMaxIter

  70. val name: String

    Definition Classes
    HasWeights

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

    Definition Classes
    AnyRef

  72. final def notify(): Unit

    Definition Classes
    AnyRef

  73. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  74. final val numCorrections: IntParam

  75. def optimize(data: RDD[(Double, Vector)], initialWeights: Vector): Vector

    Definition Classes
    LogisticRegressionLBFSG → Optimizer

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

    Definition Classes
    Params

  77. final val preInitIntercept: BooleanParam

  78. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  79. final val regParam: DoubleParam

    Definition Classes
    HasRegParam

  80. val regularizeLast: BooleanParam

    Definition Classes
    HasRegularizeLast

  81. def save(path: String): Unit

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

  82. final def set(paramPair: ParamPair[_]): LogisticRegressionLBFSG.this.type

    Attributes
    protected
    Definition Classes
    Params

  83. final def set(param: String, value: Any): LogisticRegressionLBFSG.this.type

    Attributes
    protected
    Definition Classes
    Params

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

    Definition Classes
    Params

  85. def setBatchSize(value: Int): LogisticRegressionLBFSG.this.type

    Definition Classes
    HasBatchSize

  86. def setCacheTrainData(value: Boolean): LogisticRegressionLBFSG.this.type

    Definition Classes
    HasCacheTrainData

  87. final def setDefault(paramPairs: ParamPair[_]*): LogisticRegressionLBFSG.this.type

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

  89. def setElasticNetParam(value: Double): LogisticRegressionLBFSG.this.type

  90. def setFeaturesCol(value: String): LogisticRegressionLBFSG

    Definition Classes
    Predictor

  91. def setLabelCol(value: String): LogisticRegressionLBFSG

    Definition Classes
    Predictor

  92. def setMaxIter(value: Int): LogisticRegressionLBFSG.this.type

  93. def setPreInitIntercept(value: Boolean): LogisticRegressionLBFSG.this.type

  94. def setPredictionCol(value: String): LogisticRegressionLBFSG

    Definition Classes
    Predictor

  95. def setRegParam(value: Double): LogisticRegressionLBFSG.this.type

  96. def setRegularizeLast(value: Boolean): LogisticRegressionLBFSG.this.type

    Definition Classes
    HasRegularizeLast

  97. def setTol(value: Double): LogisticRegressionLBFSG.this.type

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

    Definition Classes
    AnyRef

  99. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  100. final val tol: DoubleParam

    Definition Classes
    HasTol

  101. def train(dataset: DataFrame): LogisticRegressionModel

    Attributes
    protected
    Definition Classes
    LinearRegressor → Predictor

  102. def transformSchema(schema: StructType): StructType

    Definition Classes
    Predictor → PipelineStage

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

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  104. val uid: String

    Definition Classes
    LogisticRegressionLBFSG → LinearRegressor → Identifiable

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

    Attributes
    protected
    Definition Classes
    PredictorParams

  106. def validateParams(): Unit

    Definition Classes
    Params

  107. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  110. val weight: String

    Definition Classes
    HasWeights

  111. val weights: Block

    Definition Classes
    HasWeights

  112. def write: MLWriter

    Definition Classes
    DefaultParamsWritable → MLWritable

Inherited from HasBatchSize

Inherited from HasRegularizeLast

Inherited from HasElasticNetParam

Inherited from Optimizer

Inherited from HasMaxIter

Inherited from HasTol

Inherited from HasRegParam

Inherited from LinearRegressor[LogisticRegressionModel, LogisticRegressionLBFSG, LogisticRegressionLBFSG]

Inherited from HasCacheTrainData

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from LinearEstimator[LogisticRegressionModel, LogisticRegressionLBFSG]

Inherited from HasWeights

Inherited from LinearModelParams

Inherited from SummarizableEstimator[LogisticRegressionModel]

Inherited from Predictor[Vector, LogisticRegressionLBFSG, LogisticRegressionModel]

Inherited from PredictorParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from HasLabelCol

Inherited from Estimator[LogisticRegressionModel]

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