keras (version 2.2.4)

keras_model_sequential: Keras Model composed of a linear stack of layers

Description

Keras Model composed of a linear stack of layers

Usage

keras_model_sequential(layers = NULL, name = NULL)

Arguments

layers

List of layers to add to the model

name

Name of model

See Also

Other model functions: compile.keras.engine.training.Model, evaluate.keras.engine.training.Model, evaluate_generator, fit.keras.engine.training.Model, fit_generator, get_config, get_layer, keras_model, multi_gpu_model, pop_layer, predict.keras.engine.training.Model, predict_generator, predict_on_batch, predict_proba, summary.keras.engine.training.Model, train_on_batch

Examples

Run this code
# NOT RUN {
 
library(keras)

model <- keras_model_sequential() 
model %>% 
  layer_dense(units = 32, input_shape = c(784)) %>% 
  layer_activation('relu') %>% 
  layer_dense(units = 10) %>% 
  layer_activation('softmax')

model %>% compile(
  optimizer = 'rmsprop',
  loss = 'categorical_crossentropy',
  metrics = c('accuracy')
)
# }

Run the code above in your browser using DataCamp Workspace