ParamType

Type Members

type ParamType = Value
class Val extends Value with Serializable

Attributes
protected
Definition Classes
Enumeration
Annotations
@SerialVersionUID()
abstract class Value extends Ordered[Value] with Serializable

Definition Classes
Enumeration
Annotations
@SerialVersionUID()
class ValueSet extends AbstractSet[Value] with SortedSet[Value] with SortedSetLike[Value, ValueSet] with Serializable

Definition Classes
Enumeration

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def Value(i: Int, name: String): Value

Attributes
protected
Definition Classes
Enumeration
final def Value(name: String): Value

Attributes
protected
Definition Classes
Enumeration
final def Value(i: Int): Value

Attributes
protected
Definition Classes
Enumeration
final def Value: Value

Attributes
protected
Definition Classes
Enumeration
val activation: Value
val adaptiveRate: Value
val addIntercept: Value
val alpha: Value

R(w) = alpha * L1 + (1 - alpha) * L2: 0 -> ridge; 1 -> lasso
final def apply(x: Int): Value

Definition Classes
Enumeration
final def asInstanceOf[T0]: T0

Definition Classes
Any
val autoencoder: Value
val backend: Value
val balanceClasses: Value
val betaEpsilon: Value
val booster: Value
val classificationStop: Value
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val convergenceTol: Value
val dartNormalizeType: Value
val elasticAveraging: Value
val epochs: Value
val epsilon: Value
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
val estimateK: Value
val family: Value
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
val gammaX: Value
val gammaY: Value
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
val gradient: Value
val gradientEpsilon: Value
val growPolicy: Value
def hashCode(): Int

Definition Classes
AnyRef → Any
val hidden: Value
val hiddenDropoutRatios: Value
val imputeOriginal: Value
val initGLRM: Value
val initKMM: Value
val initLearningRate: Value
val initStepSize: Value
val initialWeightDistribution: Value
val initialWeightScale: Value
val inputDropoutRatio: Value
val intercept: Value
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val k: Value
val l1: Value
val l2: Value
val lambda: Value

lambda * R(w): 0 -> no regularizer
val lambdaSearch: Value
val laplace: Value
val loss: Value
val lossGLRMCat: Value
val lossGLRMNum: Value
val maxDepth: Value
final def maxId: Int

Definition Classes
Enumeration
val maxIterations: Value
val maxModels: Value
val maxRuntimeSecs: Value
val maxW2: Value
val minStepSize: Value
val minWordFreq: Value
val miniBatchFraction: Value
val miniBatchSize: Value
val missingValuesHandling: Value
val momentumRamp: Value
val momentumStable: Value
val momentumStart: Value
val nbins: Value
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
val nesterovAcceleratedGradient: Value
var nextId: Int

Attributes
protected
Definition Classes
Enumeration
var nextName: Iterator[String]

Attributes
protected
Definition Classes
Enumeration
val normModel: Value
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val ntrees: Value
val objectiveEpsilon: Value
val rate: Value
val rateAnnealing: Value
val rateDecay: Value
def readResolve(): AnyRef

Attributes
protected
Definition Classes
Enumeration
val recoverSVD: Value
val regAlpha: Value
val regLambda: Value
val regParam: Value
val regressionStop: Value
val regularizationX: Value
val regularizationY: Value
val rho: Value
val scoreTrainingSamples: Value
val scoreValidationSamples: Value
val scoreValidationSampling: Value
val sentSampleRate: Value
val solver: Value
val standardize: Value
val stepSize: Value
val stoppingMetric: Value

All Models: early stopping Shared Model Parameters
All Models: early stopping Shared Model Parameters
val stoppingRounds: Value

All Models: early stopping Shared Model Parameters
All Models: early stopping Shared Model Parameters
val stoppingTolerance: Value

All Models: early stopping Shared Model Parameters
All Models: early stopping Shared Model Parameters
val svdMethod: Value
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val threshold: Value
def toString(): String

Definition Classes
Enumeration → AnyRef → Any
val trainSamplesPerIteration: Value
val treeMethod: Value
val updater: Value
def values: ValueSet

Definition Classes
Enumeration
val vecSize: Value
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
val windowSize: Value
final def withName(s: String): Value

Definition Classes
Enumeration
val wordModel: Value

Related Doc: package learning

object ParamType extends Enumeration

Type Members

type ParamType = Value

class Val extends Value with Serializable

abstract class Value extends Ordered[Value] with Serializable

class ValueSet extends AbstractSet[Value] with SortedSet[Value] with SortedSetLike[Value, ValueSet] with Serializable

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def Value(i: Int, name: String): Value

final def Value(name: String): Value

final def Value(i: Int): Value

final def Value: Value

val activation: Value

val adaptiveRate: Value

val addIntercept: Value

val alpha: Value

final def apply(x: Int): Value

final def asInstanceOf[T0]: T0

val autoencoder: Value

val backend: Value

val balanceClasses: Value

val betaEpsilon: Value

val booster: Value

val classificationStop: Value

def clone(): AnyRef

val convergenceTol: Value

val dartNormalizeType: Value

val elasticAveraging: Value

val epochs: Value

val epsilon: Value

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

val estimateK: Value

val family: Value

def finalize(): Unit

val gammaX: Value

val gammaY: Value

final def getClass(): Class[_]

val gradient: Value

val gradientEpsilon: Value

val growPolicy: Value

def hashCode(): Int

val hidden: Value

val hiddenDropoutRatios: Value

val imputeOriginal: Value

val initGLRM: Value

val initKMM: Value

val initLearningRate: Value

val initStepSize: Value

val initialWeightDistribution: Value

val initialWeightScale: Value

val inputDropoutRatio: Value

val intercept: Value

final def isInstanceOf[T0]: Boolean

val k: Value

val l1: Value

val l2: Value

val lambda: Value

val lambdaSearch: Value

val laplace: Value

val loss: Value

val lossGLRMCat: Value

val lossGLRMNum: Value

val maxDepth: Value

final def maxId: Int

val maxIterations: Value

val maxModels: Value

val maxRuntimeSecs: Value

val maxW2: Value

val minStepSize: Value

val minWordFreq: Value

val miniBatchFraction: Value

val miniBatchSize: Value

val missingValuesHandling: Value

val momentumRamp: Value

val momentumStable: Value