KernelRidgeRegression

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def trainWithL2[T](trainKernelMat: KernelMatrix, labels: RDD[DenseVector[Double]], lambda: Double, blockSize: Int, numEpochs: Int, blockPermuter: Option[Long], blocksBeforeCheckpoint: Int = 25)(implicit arg0: ClassTag[T]): Seq[DenseMatrix[Double]]

Solves a linear system of the form (K + \lambda * I) * W = Y using Gauss-Seidel based Block Coordinate Descent as described in http://arxiv.org/abs/1602.05310
Solves a linear system of the form (K + \lambda * I) * W = Y using Gauss-Seidel based Block Coordinate Descent as described in http://arxiv.org/abs/1602.05310
K is assumed to be a symmetric kernel matrix generated using a kernel generator.
labels
training labels RDD
lambda
L2 regularization parameter
blockSize
number of columns per block of Gauss-Seidel solve
numEpochs
number of passes of co-ordinate descent to run
blockPermuter
seed to use for permuting column blocks
blocksBeforeCheckpoint
frequency at which intermediate data should be checkpointed
returns
a model that can be applied on test data.
def updateModel(model: RDD[IndexedSeq[DenseMatrix[Double]]], wBlockNewBC: Seq[Broadcast[DenseMatrix[Double]]], blockIdxsBC: Broadcast[Array[Int]], preFixLengthsBC: Broadcast[Array[Int]]): RDD[IndexedSeq[DenseMatrix[Double]]]
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Related Docs: class KernelRidgeRegression | package learning

object KernelRidgeRegression extends Logging with Serializable

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final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

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

def logTrace(msg: ⇒ String): Unit

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

def logWarning(msg: ⇒ String): Unit

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

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

def toString(): String

def trainWithL2[T](trainKernelMat: KernelMatrix, labels: RDD[DenseVector[Double]], lambda: Double, blockSize: Int, numEpochs: Int, blockPermuter: Option[Long], blocksBeforeCheckpoint: Int = 25)(implicit arg0: ClassTag[T]): Seq[DenseMatrix[Double]]

def updateModel(model: RDD[IndexedSeq[DenseMatrix[Double]]], wBlockNewBC: Seq[Broadcast[DenseMatrix[Double]]], blockIdxsBC: Broadcast[Array[Int]], preFixLengthsBC: Broadcast[Array[Int]]): RDD[IndexedSeq[DenseMatrix[Double]]]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

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