MLUtils

Convenience functions for machine learning tasks

This object contains convenience functions for machine learning tasks:

- readLibSVM: Reads a libSVM/SVMLight input file and returns a data set of LabeledVector. The file format is specified [http://svmlight.joachims.org/ here].

- writeLibSVM: Writes a data set of LabeledVector in libSVM/SVMLight format to disk. THe file format is specified [http://svmlight.joachims.org/ here].

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def readLibSVM(env: ExecutionEnvironment, filePath: String): DataSet[LabeledVector]

Reads a file in libSVM/SVMLight format and converts the data into a data set of LabeledVector.
Reads a file in libSVM/SVMLight format and converts the data into a data set of LabeledVector. The dimension of the LabeledVector is determined automatically.
Since the libSVM/SVMLight format stores a vector in its sparse form, the LabeledVector will also be instantiated with a SparseVector.
env
executionEnvironment ExecutionEnvironment
filePath
Path to the input file
returns
DataSet of LabeledVector containing the information of the libSVM/SVMLight file
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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def writeLibSVM(filePath: String, labeledVectors: DataSet[LabeledVector]): DataSink[String]

Writes a DataSet of LabeledVector to a file using the libSVM/SVMLight format.
Writes a DataSet of LabeledVector to a file using the libSVM/SVMLight format.
filePath
Path to output file
labeledVectors
DataSet of LabeledVector to write to disk

Related Doc: package ml

object MLUtils

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

val DIMENSION: String

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

def readLibSVM(env: ExecutionEnvironment, filePath: String): DataSet[LabeledVector]

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

def writeLibSVM(filePath: String, labeledVectors: DataSet[LabeledVector]): DataSink[String]

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