Kendall

Results 32 comments of Kendall

FIX Correct `GaussianMixture.weights_` normalization

Would it be helpful if I develop a minimal reproducible example? My plan was to do something similar to the gist linked in #23032 under `Steps/Code to Reproduce`? Thoughts?

FIX Correct `GaussianMixture.weights_` normalization

@jjerphan I've created a minimal reproducible example that prints `self.weights_` of `GaussianMixture` in the following [gist](https://gist.github.com/kasmith11/e91ec5b99a2ca295423ba728954ed17a) that heavily leans on the example outlined in the Sklearn documentation. This prints the...

Weights are being normalized using number of samples as opposed to sum in GaussianMixture

I can work on this if still available.

Make all estimators use `_validate_params`

Working on TSNE

Make all estimators use `_validate_params`

> Working on TSNE I recently pulled the most recent changes and `_parameter_constraints` were added to `sklearn/manifold/_t_sne.py`. "TSNE" was also removed from `PARAM_VALIDATION_ESTIMATORS_TO_IGNORE` in `sklearn/test/test_common.py`. Is there no longer a...

Make all estimators use `_validate_params`

> @kasmith11 indeed a PR adding param validation has been submitted a few weeks ago and was merged a few days ago, so this estimator is done. But there are...

Make all estimators use `_validate_params`

Working on `KernelPCA`

Make all estimators use `_validate_params`

Working on `SplineTransformer`

Make all estimators use `_validate_params`

Working on `SpectralEmbedding`

MAINT Parameters validation for `SpectralEmbedding`

Thank you. @jeremiedbb