CovarianceFunction

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final def !=(arg0: Any): Boolean

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final def ##(): Int

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final def ==(arg0: Any): Boolean

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def apply[T](phi: (Map[String, Double]) ⇒ (T, T) ⇒ Double)(s: Map[String, Double]): CovarianceFunction[T, Double, DenseMatrix[Double]] with LocalSVMKernel[T]

Create a kernel from a symmetric function.
Create a kernel from a symmetric function.
K(x,y) = f(state)(x,y)
phi
A function which for every state outputs a symmetric kernel evaluation function for inputs.
s
The (beginning) state of the kernel.
def apply[T](phi: DataPipe[T, DenseVector[Double]])(implicit e: InnerProductSpace[DenseVector[Double], Double]): FeatureMapCovariance[T, DenseVector[Double]]

Create a kernel from a feature mapping.
Create a kernel from a feature mapping. K(x,y) = phi^T(x) . phi(y)
phi
A general non linear transformation as a DataPipe from the domain to a multidimensional vector.
returns
A kernel instance defined for that particular feature transformation.
def apply[T](phi: (T) ⇒ DenseVector[Double])(implicit e: InnerProductSpace[DenseVector[Double], Double]): FeatureMapCovariance[T, DenseVector[Double]]

Create a kernel from a feature mapping.
Create a kernel from a feature mapping. K(x,y) = phi^T(x) . phi(y)
phi
A general non linear transformation from the domain to a multidimensional vector.
returns
A kernel instance defined for that particular feature transformation.
final def asInstanceOf[T0]: T0

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def clone(): AnyRef

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

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def equals(arg0: Any): Boolean

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def finalize(): Unit

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protected[java.lang]
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@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

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def hashCode(): Int

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final def isInstanceOf[T0]: Boolean

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final def ne(arg0: AnyRef): Boolean

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final def notify(): Unit

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final def notifyAll(): Unit

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

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def toString(): String

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final def wait(): Unit

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

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final def wait(arg0: Long): Unit

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Related Docs: class CovarianceFunction | package kernels

object CovarianceFunction extends Serializable

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def apply[T](phi: (Map[String, Double]) ⇒ (T, T) ⇒ Double)(s: Map[String, Double]): CovarianceFunction[T, Double, DenseMatrix[Double]] with LocalSVMKernel[T]

def apply[T](phi: DataPipe[T, DenseVector[Double]])(implicit e: InnerProductSpace[DenseVector[Double], Double]): FeatureMapCovariance[T, DenseVector[Double]]

def apply[T](phi: (T) ⇒ DenseVector[Double])(implicit e: InnerProductSpace[DenseVector[Double], Double]): FeatureMapCovariance[T, DenseVector[Double]]

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

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

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