SVM

final def !=(arg0: Any): Boolean

final def ##(): Int

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

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

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

def clone(): AnyRef

def copy(extra: ParamMap): SVM

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

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

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

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

def explainParams(): String

def extractLabeledPoints(dataset: Dataset[_], numClasses: Int): RDD[LabeledPoint]

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

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

final val featuresCol: Param[String]

def finalize(): Unit

def fit(dataset: Dataset[_]): SVMModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[SVMModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): SVMModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): SVMModel

final val fitIntercept: BooleanParam

Param for whether to fit the intercept.

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

final def getClass(): Class[_]

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

final def getFeaturesCol: String

final def getFitIntercept: Boolean

final def getLabelCol: String

final def getMiniBatchFraction: Double

def getNumClasses(dataset: Dataset[_], maxNumClasses: Int): Int

final def getNumIterations: Int

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

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

final def getPredictionCol: String

final def getProbabilityCol: String

final def getRawPredictionCol: String

final def getRegParam: Double

final def getStepSize: Double

final def getThreshold: Double

def getThresholds: Array[Double]

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

def hasParam(paramName: String): Boolean

def hashCode(): Int

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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

final def isInstanceOf[T0]: Boolean

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

def isTraceEnabled(): Boolean

final val labelCol: Param[String]

def log: Logger

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

def logDebug(msg: ⇒ String): Unit

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

def logError(msg: ⇒ String): Unit

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

def logInfo(msg: ⇒ String): Unit

def logName: String

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

def logTrace(msg: ⇒ String): Unit

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

def logWarning(msg: ⇒ String): Unit

final val miniBatchFraction: DoubleParam

Param for number of iterations.

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final val numIterations: IntParam

Param for number of iterations.

lazy val params: Array[Param[_]]

final val predictionCol: Param[String]

final val probabilityCol: Param[String]

final val rawPredictionCol: Param[String]

final val regParam: DoubleParam

Param for number of iterations.

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

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

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

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

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

def setFeaturesCol(value: String): SVM

def setFitIntercept(value: Boolean): SVM.this.type

def setLabelCol(value: String): SVM

def setMiniBatchFraction(value: Double): SVM.this.type

def setNumIterations(value: Int): SVM.this.type

def setPredictionCol(value: String): SVM

def setProbabilityCol(value: String): SVM

def setRawPredictionCol(value: String): SVM

def setRegParam(value: Double): SVM.this.type

def setStepSize(value: Double): SVM.this.type

def setThreshold(value: Double): SVM.this.type

def setThresholds(value: Array[Double]): SVM

final val stepSize: DoubleParam

Param for step size.

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

final val threshold: DoubleParam

Param for threshold.

final val thresholds: DoubleArrayParam

def toString(): String

def train(dataset: Dataset[_]): SVMModel

def transformSchema(schema: StructType): StructType

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

val uid: String

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

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def validateParams(): Unit