pub struct FittedTfIdfVectorizer { /* private fields */ }Expand description
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
sourceimpl FittedTfIdfVectorizer
impl FittedTfIdfVectorizer
sourcepub fn vocabulary(&self) -> &Vec<String>ⓘNotable traits for Vec<u8, A>impl<A> Write for Vec<u8, A> where
A: Allocator,
pub fn vocabulary(&self) -> &Vec<String>ⓘNotable traits for Vec<u8, A>impl<A> Write for Vec<u8, A> where
A: Allocator,
A: Allocator,
Constains all vocabulary entries, in the same order used by the transform method.
sourcepub fn method(&self) -> &TfIdfMethod
pub fn method(&self) -> &TfIdfMethod
Returns the inverse document frequency method used in the tansform method
sourcepub fn transform<T: ToString, D: Data<Elem = T>>(
&self,
x: &ArrayBase<D, Ix1>
) -> CsMat<f64>
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>
Auto Trait Implementations
impl !RefUnwindSafe for FittedTfIdfVectorizer
impl Send for FittedTfIdfVectorizer
impl !Sync for FittedTfIdfVectorizer
impl Unpin for FittedTfIdfVectorizer
impl UnwindSafe for FittedTfIdfVectorizer
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcepub fn borrow_mut(&mut self) -> &mut T
pub fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more