(self, attributes, x, n_vals)
return JaccardModel(attributes, self.axis, self.impute,
                            ps, self.callback)
Return a model for computation of Jaccard values. The model stores
        frequencies of non-zero values per each column.
Return a model for computation of Jaccard values. The model stores
        frequencies of non-zero values per each column.
Return a model for computation of Jaccard values . The model stores frequencies of non - zero values per each column .
def fit_rows(self, attributes, x, n_vals):
        """
        Return a model for computation of Jaccard values. The model stores
        frequencies of non-zero values per each column.
        """
        if sp.issparse(x):
            ps = x.getnnz(axis=0)
        else:
            ps = np.fromiter(
                (_distance.p_nonzero(x[:, col]) for col in range(len(n_vals))),
                dtype=np.double, count=len(n_vals))
        return JaccardModel(attributes, self.axis, self.impute,
                            ps, self.callback)
def fit_rows ( self , attributes , x , n_vals ) : if sp . issparse ( x ) : ps = x . getnnz ( axis = 0 ) else : ps = np . fromiter ( ( _distance . p_nonzero ( x [ : , col ] ) for col in range ( len ( n_vals ) ) ) , dtype = np . double , count = len ( n_vals ) ) return JaccardModel ( attributes , self . axis , self . impute , ps , self . callback )