Name | Modified | Size | Downloads / Week |
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DeText v1.2.0 Release Note source code.tar.gz | 2020-05-29 | 782.5 kB | |
DeText v1.2.0 Release Note source code.zip | 2020-05-29 | 804.1 kB | |
README.md | 2020-05-29 | 788 Bytes | |
Totals: 3 Items | 1.6 MB | 0 |
Currently DeText's design for sparse feature has simple modeling power for sparse features. 1. only linear model is applied on sparse features 2. there's no interaction between sparse features and dense features (model_score = dense_score + sparse_score)
DeText v1.2.0 resolves the above limitation on sparse feature by 1. computing dense representation of sparse features 2. allowing interactions between sparse features and wide features
More specifically, the model architecture changes from
dense_score = dense_ftrs -> MLP
sparse_score = sparse_ftrs -> Linear
final_score = dense_score + sparse_score
to
sparse_emb_ftrs = sparse_ftrs -> Dense(sp_emb_size)
all_ftrs = (dense_ftrs, sparse_emb_ftrs) -> Concatenate
final_score= all_ftrs -> MLP