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Installation#

We show examples of using the REaLTabFormer for modeling and generating synthetic data from a trained model.

-

[!INFO] +

[!NOTE] The model implements an optimal stopping criterion based on the synthetic data distribution when training a non-relational tabular model. The model will stop training when the synthetic data distribution is close to the real data distribution.

Make sure to set the epochs parameter to a large number to allow the model to fit the data better. diff --git a/searchindex.js b/searchindex.js index 9528a77..7de8300 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["autoapi/index", "autoapi/realtabformer/__main__/index", "autoapi/realtabformer/data_utils/index", "autoapi/realtabformer/index", "autoapi/realtabformer/realtabformer/index", "autoapi/realtabformer/rtf_analyze/index", "autoapi/realtabformer/rtf_datacollator/index", "autoapi/realtabformer/rtf_exceptions/index", "autoapi/realtabformer/rtf_sampler/index", "autoapi/realtabformer/rtf_trainer/index", "autoapi/realtabformer/rtf_validators/index", "index"], "filenames": ["autoapi/index.rst", "autoapi/realtabformer/__main__/index.rst", "autoapi/realtabformer/data_utils/index.rst", "autoapi/realtabformer/index.rst", "autoapi/realtabformer/realtabformer/index.rst", "autoapi/realtabformer/rtf_analyze/index.rst", 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