- 12 11月, 2021 1 次提交
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由 jrzaurin 提交于
First commit towards v2. Re-organized the models module and added a few new functionalities for the models in there
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- 31 8月, 2021 1 次提交
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由 jrzaurin 提交于
Added a proper implementation of transformer models when needed and re-organised the transformers module for clarity
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- 09 8月, 2021 1 次提交
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由 jrzaurin 提交于
Added cont norm options for all tabular models. Optimize cat embed for transformer models. Adjusted tab preprocessors for transformer models.
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- 06 8月, 2021 1 次提交
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由 jrzaurin 提交于
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- 03 8月, 2021 1 次提交
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由 jrzaurin 提交于
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- 11 3月, 2021 1 次提交
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由 jrzaurin 提交于
added explain and compute feature importance methods to the trainer. Need to add error handling and messaging since these funcionalities are intended only for tabnet. Move the general_utils module to the training module and rename it as trainer_utils. Adapted the create_explain_matrix function to WideDeep
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- 05 3月, 2021 1 次提交
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由 jrzaurin 提交于
finished implementing TabNet encoder. Next I need to implement the interpretability methods. Also adjusted WideDeep class to be able to work with TabNet. Renamed some example scripts to be consistent with each other
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- 02 3月, 2021 1 次提交
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由 jrzaurin 提交于
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- 08 8月, 2020 1 次提交
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由 jrzaurin 提交于
#18 Implementation of the Linear model that is the wide component via an Embedding layer. This helps optimize speed and memory usage. Adapted all the submodules accordingly
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- 27 6月, 2020 1 次提交
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由 jrzaurin 提交于
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- 03 2月, 2020 1 次提交
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由 jrzaurin 提交于
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- 02 2月, 2020 1 次提交
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由 jrzaurin 提交于
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- 25 10月, 2019 1 次提交
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由 jrzaurin 提交于
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- 24 10月, 2019 1 次提交
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由 jrzaurin 提交于
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- 23 10月, 2019 1 次提交
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由 jrzaurin 提交于
Added support for sparse matrices. Added the possibility of using a head for the deep branch. Started with the examples
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- 20 10月, 2019 2 次提交
- 11 10月, 2019 1 次提交
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由 jrzaurin 提交于
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- 03 10月, 2019 2 次提交
- 01 10月, 2019 1 次提交
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由 jrzaurin 提交于
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- 25 9月, 2019 2 次提交
- 06 5月, 2019 1 次提交
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由 jrzaurin 提交于
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