Keras模型-三级标签的自定义精度函数

from keras import backend as K

def custom_accuracy(y_true, y_pred):
    return K.mean(K.equal(y_true, K.round(y_pred)), axis=-1)

def custom_f1_score(y_true, y_pred):
    true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)), axis=0)
    predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)), axis=0)
    possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)), axis=0)
    precision = true_positives / (predicted_positives + K.epsilon())
    recall = true_positives / (possible_positives + K.epsilon())
    f1_scores = 2 * (precision * recall) / (precision + recall + K.epsilon())
    return K.mean(f1_scores)

def custom_top_k_accuracy(y_true, y_pred, k=5):
    return K.mean(K.in_top_k(y_pred, K.argmax(y_true, axis=-1), k), axis=-1)