小编Hai*_*Ass的帖子

我知道 mse 将以相同的方式对待实际 - 预测和预测 - 实际。我想编写一个自定义损失函数，使得预测 > 实际的惩罚大于实际 > 预测 假设我将因预测 > 实际而受到 2 倍的惩罚。我将如何实现这样的功能

import numpy as np

from keras.models import Model
from keras.layers import Input

import keras.backend as K
from keras.engine.topology import Layer
from keras.layers.core import  Dense

from keras import objectives

def create_model():
    # define the size
    input_size = 6
    hidden_size = 15;
    # definte the model
    model = Sequential()
    model.add(Dense(input_size, input_dim=input_size, kernel_initializer='normal', activation='relu'))
    model.add(Dense(hidden_size, kernel_initializer='normal', activation='relu'))
    model.add(Dense(1, kernel_initializer='normal'))

    # mse is used as loss for the …