pyspark.mllib.classification.NaiveBayes

Class NaiveBayes

object --+ | NaiveBayes

Instance Methods

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __init__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Class Methods

train(cls, data, lambda_=1.0)
Train a Naive Bayes model given an RDD of (label, features) vectors.

source code

Properties

Inherited from object: __class__

Method Details

train(cls, data, lambda_=1.0)
Class Method

source code

Train a Naive Bayes model given an RDD of (label, features) vectors.

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).

Parameters:

data - RDD of NumPy vectors, one per element, where the first coordinate is the label and the rest is the feature vector (e.g. a count vector).
lambda_ - The smoothing parameter

Class NaiveBayes

train(cls, data, lambda_=1.0) Class Method

train(cls, data, lambda_=1.0)
Class Method