antoinedemathelin/wann
Adversarial Weighting for Domain Adaptation in Regression
This tool helps data scientists and machine learning engineers adapt existing regression models to new, but related, datasets. If you have a model trained on one set of data (source) and want it to perform well on a slightly different, target dataset without retraining from scratch, this method adjusts the importance of your original data points. It takes your trained regression model and the new target data, outputting a re-weighted model that performs better on the target domain.
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Use this if you need to quickly adapt a pre-trained regression model to a new dataset where the underlying data distribution has shifted slightly, saving significant time compared to building a new model from scratch.
Not ideal if your new dataset is dramatically different from your original training data, or if you are not working with regression tasks.
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Last pushed
Jun 01, 2022
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