Tokenizes numeric features into a dense embedding.
For an input of shape (batch, n_features) the output shape is (batch, n_features, d_token).
Usage
nn_tokenizer_num(n_features, d_token, bias, initialization)
Arguments
- n_features
(integer(1))
The number of features.
- d_token
(integer(1))
The dimension of the embedding.
- bias
(logical(1))
Whether to use a bias.
- initialization
(character(1))
The initialization method for the embedding weights. Possible values are "uniform"
and "normal".
References
Gorishniy Y, Rubachev I, Khrulkov V, Babenko A (2021).
“Revisiting Deep Learning for Tabular Data.”
arXiv, 2106.11959.
