Struct NaiveBayes

pub struct NaiveBayes { /* private fields */ }

Naive Bayes classifier

Implementations

impl Classifier

pub fn new() -> Classifier

Creates a new classifier

pub fn add_document_tokenized(&mut self, document: &Vec<String>, label: &String)

Takes a document that has been tokenized into a vector of strings and a label and adds the document to the list of documents that the classifier is aware of and will train on next time the train() method is called

pub fn add_document(&mut self, document: &String, label: &String)

Takes a document and a label and tokenizes the document by breaking on whitespace characters. The document is added to the list of documents that the classifier is aware of and will train on next time the train() method is called

pub fn add_documents(&mut self, examples: &Vec<(String, String)>)

Adds a list of (document, label) tuples to the classifier

pub fn add_documents_tokenized(&mut self, examples: &Vec<(Vec<String>, String)>)

Adds a list of (tokenized document, label) tuples to the classifier

pub fn get_labels(&self) -> Vec<String>

Gets a vector of all of the labels that the classifier has seen so far

pub fn set_smoothing(&mut self, smoothing: f64)

Sets the smoothing value (must be greater than 0.0)

pub fn train(&mut self)

Trains the classifier on the documents that have been observed so far

pub fn classify_tokenized(&self, document: &Vec<String>) -> String

Takes an unlabeled document that has been tokenized into a vector of strings and then computes a classifying label for the document

pub fn classify(&self, document: &String) -> String

Takes an unlabeled document and tokenizes it by breaking on spaces and then computes a classifying label for the document

pub fn get_document_probabilities_tokenized( &self, document: &Vec<String>, ) -> Vec<(String, f64)>

Similar to classify but instead of returning a single label, returns all labels and the probabilities of each one given the document

pub fn get_document_probabilities( &self, document: &String, ) -> Vec<(String, f64)>

Similar to classify but instead of returning a single label, returns all labels and the probabilities of each one given the document

pub fn to_json(&self) -> String

Encodes the classifier as a JSON string.

pub fn from_json(encoded: &str) -> Classifier

Builds a new classifier from a JSON string

Trait Implementations

impl Clone for Classifier

fn clone(&self) -> Classifier

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Classifier

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Decodable for Classifier

fn decode<__D: Decoder>(d: &mut __D) -> Result<Classifier, __D::Error>

Deserialize a value using a Decoder.

impl Encodable for Classifier

fn encode<__S: Encoder>(&self, s: &mut __S) -> Result<(), __S::Error>

Serialize a value using an Encoder.