Interceptor

Type Members

class Uninterceptor[M <: LinearModel[M]] extends PredefinedDataTransformer[M, Uninterceptor[M]]

Model transformer which moves weight trained for an intercept into the intercept parameter of the model (so far supported only for linear models).
Model transformer which moves weight trained for an intercept into the intercept parameter of the model (so far supported only for linear models). This helps to avoid extra overhead when predicting.
class UninterceptorComposite[M <: LinearModel[M], C <: CombinedModel[M, C]] extends PredefinedDataTransformer[C, UninterceptorComposite[M, C]]

Value Members

final def !=(arg0: Any): Boolean

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

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final def ==(arg0: Any): Boolean

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AnyRef → Any
def appendBias(vector: Vector): Vector

Adds 1 to the end of a vector.
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
final def eq(arg0: AnyRef): Boolean

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def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

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

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def hashCode(): Int

Definition Classes
AnyRef → Any
def intercept[M <: LinearModel[M]](estimator: SummarizableEstimator[M], features: String = "features"): UnwrappedStage[M, Uninterceptor[M]]

Adds an intercept/unintercept stage to the estimator of a linear model.
Adds an intercept/unintercept stage to the estimator of a linear model.
estimator
Nested estimator with linear model as result.
returns
Estimator which produce a linear model with explicit intercept.
def interceptComposite[M <: LinearModel[M], C <: CombinedModel[M, C]](estimator: SummarizableEstimator[C], features: String = "features"): UnwrappedStage[C, UninterceptorComposite[M, C]]

Adds an intercept/unintercept stage to the composite estimator with nested linear models.
Adds an intercept/unintercept stage to the composite estimator with nested linear models.
estimator
Nested composite estimator built of with linear model as result.
returns
Estimator which produce a combination of linear models with explicit intercept.
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def load(path: String): Interceptor

Definition Classes
MLReadable
Annotations
@Since( "1.6.0" )
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
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final def notifyAll(): Unit

Definition Classes
AnyRef
def read: MLReader[Interceptor]

Definition Classes
DefaultParamsReadable → MLReadable
def removeBias(vector: Vector): Vector

Removes last column of a vector.
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
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def transformModel[M <: LinearModel[M]](model: M): M
final def wait(): Unit

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

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

Definition Classes
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Annotations
@throws( ... )

Related Docs: class Interceptor | package odkl

object Interceptor extends DefaultParamsReadable[Interceptor] with Serializable

Type Members

class Uninterceptor[M <: LinearModel[M]] extends PredefinedDataTransformer[M, Uninterceptor[M]]

class UninterceptorComposite[M <: LinearModel[M], C <: CombinedModel[M, C]] extends PredefinedDataTransformer[C, UninterceptorComposite[M, C]]

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def appendBias(vector: Vector): Vector

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

def intercept[M <: LinearModel[M]](estimator: SummarizableEstimator[M], features: String = "features"): UnwrappedStage[M, Uninterceptor[M]]

def interceptComposite[M <: LinearModel[M], C <: CombinedModel[M, C]](estimator: SummarizableEstimator[C], features: String = "features"): UnwrappedStage[C, UninterceptorComposite[M, C]]

final def isInstanceOf[T0]: Boolean

def load(path: String): Interceptor

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def read: MLReader[Interceptor]

def removeBias(vector: Vector): Vector

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

def toString(): String

def transformModel[M <: LinearModel[M]](model: M): M

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from DefaultParamsReadable[Interceptor]

Inherited from MLReadable[Interceptor]

Inherited from AnyRef

Inherited from Any

Ungrouped