Simplify fit parameters for CCATransformer and CCorATransformer
#31
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Transformers no longer take `spp` parameters when fitting. Instead, estimators now choose the appropriate `y_fit` data to pass to the transformer. This simplifies the responsibility of transformers and avoids some error checking that would have been needed otherwise. The `spp` parameter to the estimators was renamed to `y_fit` to be more general.
aazuspan
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grovduck
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May 31, 2023
We exported data from yaImpute for the five core estimators at k=5 for both unweighted (equal-weighting to all neighbors) and weighted (neighbors are weighted by their inverse distance) predictions of the y attributes. The tests assert that the predict method in each estimator is returning the same values. Note that the constructor of each estimator uses a custom function (yaimpute_weights) to the weights parameter in order to match the weighting scheme of yaImpute.
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This looks great. Ignore the commit reference above. I was trying to follow your convention of referencing both the issue and PR numbers in the commit title, but I think you sneaked this commit in there before I did ;). I ended up amending my commit message, but alas too late for this. Let's get this one merged first as I think it will have some breaking changes in #32 with the |
Sounds good, thanks! |
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This will close #30 by:
ya required parameter for fittingCCATransformerandCCorATransformer.GNNRegressorandMSNRegressorchoose the appropriate fitting data instead of the transformer.spptoy_fitthroughout.