org.apache.spark.mllib.util

DataValidators

object DataValidators extends Logging

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

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@DeveloperApi() @Since( "0.8.0" )
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  1. final def !=(arg0: AnyRef): Boolean

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  6. final def asInstanceOf[T0]: T0

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  7. val binaryLabelValidator: (RDD[LabeledPoint]) ⇒ Boolean

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

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

    returns

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

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    @Since( "1.0.0" )
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  16. def log: Logger

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  17. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

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  18. def logDebug(msg: ⇒ String): Unit

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  19. def logError(msg: ⇒ String, throwable: Throwable): Unit

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  23. def logName: String

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  24. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

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

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  27. def logWarning(msg: ⇒ String): Unit

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  28. def multiLabelValidator(k: Int): (RDD[LabeledPoint]) ⇒ Boolean

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

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

    returns

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

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    @Since( "1.3.0" )
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