org.apache.spark.mllib.util
Class DataValidators

Object
  org.apache.spark.mllib.util.DataValidators

All Implemented Interfaces:

Logging

public class DataValidators
extends Object
implements Logging

:: DeveloperApi :: A collection of methods used to validate data before applying ML algorithms.

Constructor Summary

DataValidators()

Method Summary

static scala.Function1<RDD<LabeledPoint>,Object>	binaryLabelValidator() Function to check if labels used for classification are either zero or one.
static scala.Function1<RDD<LabeledPoint>,Object>	multiLabelValidator(int k) Function to check if labels used for k class multi-label classification are in the range of {0, 1, ..., k - 1}.

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

DataValidators

public DataValidators()

Method Detail

binaryLabelValidator

public static scala.Function1<RDD<LabeledPoint>,Object> binaryLabelValidator()

Function to check if labels used for classification are either zero or one.

Returns:

True if labels are all zero or one, false otherwise.

multiLabelValidator

public static scala.Function1<RDD<LabeledPoint>,Object> multiLabelValidator(int k)

Function to check if labels used for k class multi-label classification are in the range of {0, 1, ..., k - 1}.

Parameters:

k - (undocumented)

Returns:

True if labels are all in the range of {0, 1, ..., k-1}, false otherwise.