pub(crate) fn new(freq_cutoff: usize, tsv_dense: Option<Vec<usize>>) -> Self {
        let is_dense = tsv_dense.map(|dense_counts| {
            let largest = dense_counts.iter().max().copied().unwrap_or(0) + 1;
            let mut bitmap = vec![false; largest];
            for i in dense_counts.into_iter() {
                bitmap[i] = true;
            }
            bitmap
        });

        FeaturizerConstructor {
            counts: Default::default(),
            lines: 0,
            is_dense,
            categorical_counts: Vec::new(),
            freq_cutoff,
        }
    }
/// Factorization behavior varies between tabular tsv and sparse
/// svm input. See the flag of the name `tsv_dense` for details in
/// main.rs.
///
/// Features appearing less than `freq_cutoff` times will be discarded.
Factorization behavior varies between tabular tsv and sparse
svm input. See the flag of the name `tsv_dense` for details in
main.rs.

Features appearing less than `freq_cutoff` times will be discarded.
Factorization behavior varies between tabular tsv and sparse svm input . See the flag of the name ` tsv_dense ` for details in main . rs . Features appearing less than ` freq_cutoff ` times will be discarded .
pub(crate) fn new(freq_cutoff: usize, tsv_dense: Option<Vec<usize>>) -> Self {
        let is_dense = tsv_dense.map(|dense_counts| {
            let largest = dense_counts.iter().max().copied().unwrap_or(0) + 1;
            let mut bitmap = vec![false; largest];
            for i in dense_counts.into_iter() {
                bitmap[i] = true;
            }
            bitmap
        });
        FeaturizerConstructor {
            counts: Default::default(),
            lines: 0,
            is_dense,
            categorical_counts: Vec::new(),
            freq_cutoff,
        }
    }
pub ( crate ) fn new ( freq_cutoff : usize , tsv_dense : Option < Vec < usize > > ) -> Self { let is_dense = tsv_dense . map ( | dense_counts | { let largest = dense_counts . iter ( ) . max ( ) . copied ( ) . unwrap_or ( 0 ) + 1 ; let mut bitmap = vec ! [ false largest ] ; for i in dense_counts . into_iter ( ) { bitmap [ i ] = true ; } bitmap } ) ; FeaturizerConstructor { counts : Default :: default ( ) , lines : 0 , is_dense , categorical_counts : Vec :: new ( ) , freq_cutoff , } }
Factorization behavior varies between tabular tsv and sparse
svm input.
Factorization behavior varies between tabular tsv and sparse svm input .
freq_cutoff
usize
tsv_dense
Option<Vec<usize>>
freq_cutoff
usize
tsv_dense
Option<Vec<usize>>