如何在R中使用neuralnet包实现自己的错误函数

Question

我正试图在R.中的neuralnet包中实现一个自定义的错误函数

通常使用代表误差平方和和和交叉熵的"sse"one_answers"ce"来计算误差。有人能给我提供关于如何实现自己的错误函数的详细信息吗。尽管软件包说我们可以使用自定义的错误功能，但用户Manuel对此没有任何帮助。

Answer 1

我也遇到了同样的问题。这是我收到的解决方案/帮助。你可以使用R函数的通常定义（函数（x，y）｛…｝）。因此，误差函数必须是函数（x、y）类型，其中x是拟合值，y是真值。

请参考以下示例。

library(neuralnet)
AND <- c(rep(0,7),1)
OR <- c(0,rep(1,7))
binary.data <- data.frame(expand.grid(c(0,1), c(0,1), c(0,1)), AND, OR)
set.seed(3)
print(net <- neuralnet(AND+OR~Var1+Var2+Var3,  binary.data, hidden=0, rep=10, err.fct="sse", linear.output=FALSE))
#Call: neuralnet(formula = AND + OR ~ Var1 + Var2 + Var3, data = binary.data,     hidden = 0, rep = 10, err.fct = "sse", linear.output = FALSE)
#
#10 repetitions were calculated.
#
#Error Reached Threshold Steps
#7  0.04043122185    0.008248439644   116
#5  0.04426319054    0.009619409680   124
#8  0.04698485282    0.007947430014   117
#2  0.04931335384    0.008792873261    88
#1  0.04965332555    0.009631079320    89
#4  0.05396400022    0.009092193542    96
#6  0.05488395412    0.009990028287   124
#3  0.06383087672    0.009964206587    94
#10 0.51657348285    0.008602371325    51
#9  0.52514202592    0.007890927099    40

set.seed(3)
custom <- function(x,y){1/2*(y-x)^2}
print(net <- neuralnet(AND+OR~Var1+Var2+Var3,  binary.data, hidden=0, rep=10, linear.output=FALSE, err.fct=custom))
#Call: neuralnet(formula = AND + OR ~ Var1 + Var2 + Var3, data = binary.data,     hidden = 0, rep = 10, err.fct = custom, linear.output = FALSE)
#
#10 repetitions were calculated.
#
#Error Reached Threshold Steps
#7  0.04043122185    0.008248439644   116
#5  0.04426319054    0.009619409680   124
#8  0.04698485282    0.007947430014   117
#2  0.04931335384    0.008792873261    88
#1  0.04965332555    0.009631079320    89
#4  0.05396400022    0.009092193542    96
#6  0.05488395412    0.009990028287   124
#3  0.06383087672    0.009964206587    94
#10 0.51657348285    0.008602371325    51
#9  0.52514202592    0.007890927099    40

基本上可以使用所有可以区分的错误函数。