小编Fra*_*ani的帖子

我正在尝试使用 keras for R 集成多个神经网络。为此，我想通过使用“foreach”循环来并行化不同网络的训练。

models <- list()
x_bagged <- list()
y_bagged <- list()

n_nets = 2
bag_frac <-0.7
len <- nrow(x_train)

for(i in 1:n_nets){
    sam <- sample(len, floor(bag_frac*len), replace=FALSE)
    x_bagged[[i]] <- x_train[sam,]
    y_bagged[[i]] <- y_train[sam]

    models[[i]] <- keras_model_sequential() 

models[[i]] %>% 
  layer_dense(units = 100, input_shape = ncol(x_train), activation = "relu", kernel_initializer = 'glorot_normal') %>% 
  layer_batch_normalization() %>%
  layer_dense(units = 100, activation = custom_activation, kernel_initializer = 'glorot_normal') %>%
  layer_dense(units = 1, activation = 'linear', kernel_initializer = 'glorot_normal')


    models[[i]] %>% compile( …