Update simple_deep_learning.R

exercice_1/simple_deep_learning.R

@@ -6,6 +6,7 @@ keras::install_keras(tensorflow = "cpu")
 
 library(keras)
 
+parole_train <- read.csv("/cloud/project/parole_train.txt", sep="")
 parole_train <- parole_train
 
 # Generation of 2/3 observations
@@ -35,7 +36,7 @@ model %>% layer_dense(units=128, activation = "relu", input_shape = c(256)) %>%
 
 model %>% compile(
   loss = 'categorical_crossentropy',
-  optimizer = optimizer_rmsprop(),
+  optimizer = "adam",
   metrics = c('accuracy')
 )
 
@@ -43,9 +44,10 @@ summary(model)
 
 history <- model %>% fit(
   x_train, y_train, 
-  epochs = 30, batch_size = 256, verbose=2
+  epochs = 50, batch_size = 256, verbose=2
 )
 
+
 pred.parole_train.deep <- as.array(model %>% predict(scale(data.matrix(X.test[, 1:256]))) %>% k_argmax())
 
 #Matrix of confusion