helpers.py 文件源码

def find_f_measure_threshold2(probs, labels, num_iters=100, seed=0.21):
    _, num_classes = labels.shape[0:2]
    best_thresholds = [seed] * num_classes
    best_scores = [0] * num_classes
    for t in range(num_classes):

        thresholds = list(best_thresholds)  # [seed]*num_classes
        for i in range(num_iters):
            th = i / float(num_iters)
            thresholds[t] = th
            f2 = fbeta_score(labels, probs > thresholds, beta=2, average='samples')
            if f2 > best_scores[t]:
                best_scores[t] = f2
                best_thresholds[t] = th
        print('\t(t, best_thresholds[t], best_scores[t])=%2d, %0.3f, %f' % (t, best_thresholds[t], best_scores[t]))
    print('')
    return best_thresholds, best_scores