Keras Model composed of a linear stack of layers
Keras Model composed of a linear stack of layers
keras_model_sequential(layers = NULL, name = NULL)
layers |
List of layers to add to the model |
name |
Name of model |
The first layer passed to a Sequential model should have a defined input
shape. What that means is that it should have received an input_shape or
batch_input_shape argument, or for some type of layers (recurrent,
Dense...) an input_dim argument.
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()
## 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')
)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.