def _get_scaled_f_score_from_counts(self, cat_word_counts, not_cat_word_counts, scaler_algo,
                                        beta=DEFAULT_BETA):
        '''
        scaler = self._get_scaler_function(scaler_algo)
        p_word_given_category = cat_word_counts.astype(np.float64) / cat_word_counts.sum()
        p_category_given_word = cat_word_counts.astype(np.float64) / (cat_word_counts + not_cat_word_counts)
        scores \
            = self._computer_harmoic_mean_of_probabilities_over_non_zero_in_category_count_terms(
            cat_word_counts, p_category_given_word, p_word_given_category, scaler
        )
        '''
        return ScaledFScore.get_scores(cat_word_counts, not_cat_word_counts, scaler_algo, beta=beta)
def _get_scaled_f_score_from_counts ( self , cat_word_counts , not_cat_word_counts , scaler_algo , beta = DEFAULT_BETA ) : return ScaledFScore . get_scores ( cat_word_counts , not_cat_word_counts , scaler_algo , beta = beta )
scaler = self._get_scaler_function(scaler_algo)
        p_word_given_category = cat_word_counts.astype(np.float64) / cat_word_counts.sum()
        p_category_given_word = cat_word_counts.astype(np.float64) / (cat_word_counts + not_cat_word_counts)
        scores \
            = self._computer_harmoic_mean_of_probabilities_over_non_zero_in_category_count_terms(
            cat_word_counts, p_category_given_word, p_word_given_category, scaler
        )