2999e509688a82f8be65600727a5922b5739822b,conceptnet5/vectors/evaluation/wordsim.py,,compute_semeval_score,#,309

Before Change

        low_harmonic_mean = float("NaN")
        high_harmonic_mean = float("NaN")
    else:
        acc_harmonic_mean = hmean([spearman_score["acc"], pearson_score["acc"]])
        low_harmonic_mean = hmean([spearman_score["low"], pearson_score["low"]])
        high_harmonic_mean = hmean([spearman_score["high"], pearson_score["high"]])

    return pd.Series(

After Change

        else:
            scores.append(hmean([spearman_score[interval], pearson_score[interval]]))

    return pd.Series(
        scores,
        index=intervals
    )


def evaluate_semeval_monolingual(vectors, lang):
    

Instances