meta::classify::naive_bayes Class Reference

Implements the Naive Bayes classifier, a simplistic probabilistic classifier that uses Bayes' theorem with strong feature independence assumptions. More...

#include <naive_bayes.h>

Inheritance diagram for meta::classify::naive_bayes:

Public Member Functions
	naive_bayes (std::shared_ptr< index::forward_index > idx, double alpha=default_alpha, double beta=default_beta)
	Constructor: learns class models based on a collection of training documents. More...
void	train (const std::vector< doc_id > &docs) override
	Creates a classification model based on training documents. More...
class_label	classify (doc_id d_id) override
	Classifies a document into a specific group, as determined by training data. More...
void	reset () override
	Resets any learning information associated with this classifier.
Public Member Functions inherited from meta::classify::classifier
	classifier (std::shared_ptr< index::forward_index > idx)
virtual confusion_matrix	test (const std::vector< doc_id > &docs)
	Classifies a collection document into specific groups, as determined by training data; this function will make repeated calls to classify(). More...
virtual confusion_matrix	cross_validate (const std::vector< doc_id > &input_docs, size_t k, bool even_split=false, int seed=1)
	Performs k-fold cross-validation on a set of documents. More...

Static Public Attributes
static const constexpr double	default_alpha = 0.1
	The default \(\alpha\) parameter.
static const constexpr double	default_beta = 0.1
	The default \(beta\) parameter.
static const std::string	id = "naive-bayes"
	The identifier for this classifier.

Private Attributes
util::sparse_vector< class_label, stats::multinomial< term_id > >	term_probs_
	Contains P(term|class) for each class.
stats::multinomial< class_label >	class_probs_
	Contains the number of documents in each class.

Additional Inherited Members
Protected Attributes inherited from meta::classify::classifier
std::shared_ptr< index::forward_index >	idx_
	the index that the classifer is run on

Detailed Description

Implements the Naive Bayes classifier, a simplistic probabilistic classifier that uses Bayes' theorem with strong feature independence assumptions.

Constructor & Destructor Documentation

meta::classify::naive_bayes::naive_bayes	(	std::shared_ptr< index::forward_index >	idx,
		double	alpha = default_alpha,
		double	beta = default_beta
	)

Constructor: learns class models based on a collection of training documents.

Parameters

idx	The index to run the classifier on
alpha	Optional smoothing parameter for term frequencies
beta	Optional smoothing parameter for class frequencies

Member Function Documentation

void meta::classify::naive_bayes::train ( const std::vector< doc_id > &  docs )

overridevirtual

Creates a classification model based on training documents.

Calculates \(P(term|class)\) and \(P(class)\) for all the training documents.

Parameters

docs	The training documents

Implements meta::classify::classifier.

class_label meta::classify::naive_bayes::classify ( doc_id  d_id )

overridevirtual

Classifies a document into a specific group, as determined by training data.

Parameters

d_id	The document to classify

Returns

the class it belongs to

Implements meta::classify::classifier.

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The documentation for this class was generated from the following files:

• /home/chase/projects/meta/include/classify/classifier/naive_bayes.h
• /home/chase/projects/meta/src/classify/classifier/naive_bayes.cpp