tensorflow_rnn.py 文件源码

def calc_f1_score(predictions,labels):
    predictions = np.argmax(predictions,1)
    labels = np.argmax(labels,1)
    tp = fp = tn = fn = 0
    for a,b in zip(predictions,labels):
        if a == 1:
            if a == b:
                tp += 1
            else:
                fp += 1
        else:
            if a == b:
                tn += 1
            else:
                fn += 1

    precision = ( tp / (tp + fp) ) if (tp + fp) > 0 else 0
    recall = ( tp / (tp + fn) ) if (tp + fn) > 0 else 0
    f1_score = 2*((precision * recall) / (precision + recall )) if (precision + recall) > 0 else 0
    return f1_score

#Argument handling, Copy paste from tflearn_rnn.py