word2vec_model.py 文件源码

def results(db, model, comp_func, k=1, expand_label=False):
    if k < 1:
        raise ValueError
    score_matrix = generate_cross_scores(local_db, model, comp_func, expand_label)
    labels = np.array(get_labels())

    # Sort scores in descending order
    top_score_ind = np.argsort(score_matrix[:, :score_matrix.shape[1]-2,], axis=1)
    top_score_ind = np.fliplr(top_score_ind)

    # Get top K guesses
    y_hat = []
    for i in range(k):
        y_hat.append(labels[top_score_ind[:,i]])
    y_hat = np.vstack(y_hat).T

    y = score_matrix[:, score_matrix.shape[1]-1]
    score_pool = []
    for i in range(k):
        score_pool.append((y == y_hat[:, i]).astype(int))
    score_pool = np.vstack(score_pool).T

    r = np.max(score_pool, axis=1)
    return float(np.count_nonzero(r)) / float(len(r)), score_matrix