## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(echo = TRUE, eval = FALSE) ## ----------------------------------------------------------------------------- # library(LDNN) # set.seed(12345) # #Train dummy data # X1 <- matrix(runif(500*20), nrow=500, ncol=20) # X2 <- matrix(runif(500*24), nrow=500, ncol=24) # X3 <- matrix(runif(500*24), nrow=500, ncol=24) # X4 <- matrix(runif(500*24), nrow=500, ncol=24) # X5 <- matrix(runif(500*16), nrow=500, ncol=16) # X6 <- matrix(runif(500*16), nrow=500, ncol=16) # X7 <- matrix(runif(500*16), nrow=500, ncol=16) # X8 <- matrix(runif(500*16), nrow=500, ncol=16) # X9 <- matrix(runif(500*16), nrow=500, ncol=16) # X10 <- matrix(runif(500*15), nrow=500, ncol=15) # Xif <- matrix(runif(500*232), nrow=500, ncol=232) # y <- matrix(runif(500), nrow=500, ncol=1) # #Test dummy data # X1_test <- matrix(runif(500*20), nrow=500, ncol=20) # X2_test <- matrix(runif(500*24), nrow=500, ncol=24) # X3_test <- matrix(runif(500*24), nrow=500, ncol=24) # X4_test <- matrix(runif(500*24), nrow=500, ncol=24) # X5_test <- matrix(runif(500*16), nrow=500, ncol=16) # X6_test <- matrix(runif(500*16), nrow=500, ncol=16) # X7_test <- matrix(runif(500*16), nrow=500, ncol=16) # X8_test <- matrix(runif(500*16), nrow=500, ncol=16) # X9_test <- matrix(runif(500*16), nrow=500, ncol=16) # X10_test <- matrix(runif(500*15), nrow=500, ncol=15) # Xif_test <- matrix(runif(500*232), nrow=500, ncol=232) # y_test <- matrix(runif(500), nrow=500, ncol=1) # #Create the model # model = create_model(rnn_inputs = c(20,24,24,24,16,16,16,16,16,15), # recurrent_droppout = c(0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1,0.1), # inputs = 232, # layer_dropout = c(0.1,0.1), # n_nodes_hidden_layers = c(1024,1024), # loss_function = 'mean_squared_error', # opt = 'adam', # metric = 'mean_absolute_error') # #Fit the model # fitted_model = fit_model(model = model,ver = 0, n_epoch = 1,bsize = 32,X1 = X1, X2 = X2, X3 = X3,X4 = X4,X5 = X5,X6 = X6,X7 = X7,X8 = X8,X9 = X9,X10 = X10,Xif = Xif,y = y) # #Evaluate the model on test data # evaluate_model(model = fitted_model,X1_test = X1_test, X2_test = X2_test, X3_test = X3_test,X4_test = X4_test,X5_test = X5_test,X6_test = X6_test,X7_test = X7_test,X8_test = X8_test,X9_test = X9_test,X10_test = X10_test,Xif_test = Xif_test,y_test = y_test,bsize = 32)