HyperparametersOptimizer

abstract def copy(extra: ParamMap): HyperparametersOptimizer[M]

abstract def extractConfig(row: Row): (Double, ParamMap)

In order to support correct restoration from the temporary model storage and grouped optimization we need a way to restore model configuration from its summary row of configurations block.

abstract def fit(dataset: Dataset[_]): M

abstract def transformSchema(schema: StructType): StructType

abstract val uid: String

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[_]): HyperparametersOptimizer.this.type

def clone(): AnyRef

val configurationIndexColumn: Param[String]

val configurations: Block

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

def createConfigurationsBlock(sqlContext: SQLContext, failedModels: Seq[(ParamMap, Try[M])], rankedModels: Seq[(ParamMap, M, Double)]): DataFrame

Create summary block with investigated configurations.

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

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

val errorColumn: Param[String]

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

def explainParams(): String

final def extract(model: ModelWithSummary[_]): Option[DataFrame]

def extractBestModel(sqlContext: SQLContext, failedModels: Seq[(ParamMap, Try[M])], rankedModels: Seq[(ParamMap, M, Double)]): M

Given all the history of the optimization create the resulting model with the configurations summary block.

def extractConfig(model: M): (Double, ParamMap)

val extractExpression: Param[String]

def extractImpl(model: ModelWithSummary[_]): Option[DataFrame]

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

def extractParamsAndQuality(params: ParamMap, model: M): (ParamMap, M, Double)

Extracts information of the resulting metrics from the trained model.

def finalize(): Unit

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

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

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

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

final def getClass(): Class[_]

def getConfigurationIndexColumn: String

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

def getErrorColumn: String

def getMetricsBlock: String

def getMetricsExpression: String

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

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

def getResultingMetricColumn: String

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

def hasParam(paramName: String): Boolean

def hashCode(): Int

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

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

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

val metricsBlock: Param[String]

val metricsExpression: Param[String]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

final val numThreads: IntParam

val paramNames: Param[Map[Param[_], String]]

lazy val params: Array[Param[_]]

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

val resultingMetricColumn: Param[String]

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

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

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

def setConfigurationIndexColumn(value: String): HyperparametersOptimizer.this.type

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

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

def setErrorColumn(value: String): HyperparametersOptimizer.this.type

def setExtractExpression(value: String): HyperparametersOptimizer.this.type

def setMetricsBlock(value: String): HyperparametersOptimizer.this.type

def setMetricsExpression(value: String): HyperparametersOptimizer.this.type

def setNumThreads(value: Int): HyperparametersOptimizer.this.type

def setParamNames(value: (Param[_], String)*): HyperparametersOptimizer.this.type

def setResultingMetricColumn(value: String): HyperparametersOptimizer.this.type

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

def toString(): String

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

final def wait(): Unit

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

final def wait(arg0: Long): Unit