org.apache.spark.mllib.classification

NaiveBayes

class NaiveBayes extends Serializable with Logging

Trains a Naive Bayes model given an RDD of (label, features) pairs.

This is the Multinomial NB (http://tinyurl.com/lsdw6p) which can handle all kinds of discrete data. For example, by converting documents into TF-IDF vectors, it can be used for document classification. By making every vector a 0-1 vector, it can also be used as Bernoulli NB (http://tinyurl.com/p7c96j6). The input feature values must be nonnegative.

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  1. new NaiveBayes()

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  13. def log: Logger

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  20. def logName: String

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  26. final def notify(): Unit

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  27. final def notifyAll(): Unit

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  28. def run(data: RDD[LabeledPoint]): NaiveBayesModel

    Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.

    Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.

    data

    RDD of org.apache.spark.mllib.regression.LabeledPoint.

  29. def setLambda(lambda: Double): NaiveBayes

    Set the smoothing parameter.

    Set the smoothing parameter. Default: 1.0.

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

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  31. def toString(): String

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