使用keras實現Precise, Recall, F1-socre

實現過程

from keras import backend as K
def Precision(y_true, y_pred):
    """精確率"""
    tp= K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))  # true positives
    pp= K.sum(K.round(K.clip(y_pred, 0, 1))) # predicted positives
    precision = tp/ (pp+ K.epsilon())
    return precision
    
def Recall(y_true, y_pred):
    """召回率"""
    tp = K.sum(K.round(K.clip(y_true * y_pred, 0, 1))) # true positives
    pp = K.sum(K.round(K.clip(y_true, 0, 1))) # possible positives
    recall = tp / (pp + K.epsilon())
    return recall
 
def F1(y_true, y_pred):
    """F1-score"""
    precision = Precision(y_true, y_pred)
    recall = Recall(y_true, y_pred)
    f1 = 2 * ((precision * recall) / (precision + recall + K.epsilon()))
    return f1