Description Usage Arguments Value
Word embedding + gru global average & max + 1D pooled convolution
1 2 3 | keras_gru_cnn(input_dim, embed_dim = 128, seq_len = 50, gru_dim = 64,
gru_drop = 0.2, filter_sizes = c(3, 2), n_filters = c(120, 60),
pool_size = 4, output_fun = "sigmoid", output_dim = 1)
|
input_dim |
Number of unique vocabluary/tokens |
embed_dim |
Number of word vectors |
seq_len |
Length of the input sequences |
gru_dim |
Number of lstm neurons (default 32) |
gru_drop |
default is 2 |
n_filters |
the number of convolutional filters |
pool_size |
pooling dimension (filters) |
output_fun |
Output activation function |
output_dim |
Number of neurons of the output layer |
filter_size |
the window size (kernel_size) |
keras model
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