Struct linfa_preprocessing::tf_idf_vectorization::FittedTfIdfVectorizer

pub struct FittedTfIdfVectorizer { /* private fields */ }

Counts the occurrences of each vocabulary entry, learned during fitting, in a sequence of texts and scales them by the inverse document document frequency defined by the method. Each vocabulary entry is mapped to an integer value that is used to index the count in the result.

Implementations

impl FittedTfIdfVectorizer

pub fn nentries(&self) -> usize

Number of vocabulary entries learned during fitting

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

Constains all vocabulary entries, in the same order used by the transform method.

pub fn method(&self) -> &TfIdfMethod

Returns the inverse document frequency method used in the tansform method

pub fn transform<T: ToString, D: Data<Elem = T>>(
    &self,
    x: &ArrayBase<D, Ix1>
) -> CsMat<f64>

Given a sequence of n documents, produces an array of size (n, vocabulary_entries) where column j of row i is the number of occurrences of vocabulary entry j in the text of index i, scaled by the inverse document frequency. Vocabulary entry j is the string at the j-th position in the vocabulary.

pub fn transform_files<P: AsRef<Path>>(
    &self,
    input: &[P],
    encoding: EncodingRef,
    trap: DecoderTrap
) -> CsMat<f64>

Trait Implementations

impl Clone for FittedTfIdfVectorizer

fn clone(&self) -> FittedTfIdfVectorizer

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for FittedTfIdfVectorizer

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

Formats the value using the given formatter.