lolo

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Gradient boosted trees can outperform random forests, given proper selection of hyperparameters. In lolo, gradient boosting could be a general component in learner composition, e.g. boosting two linear models against...

maxhutch

Right now, hyperparameter optimization is supported only with the bagged learner, which implements `getLoss` with out of bag estimates. A cross validation learner could give any learner a reasonable `getLoss`...

maxhutch

Bumps [scikit-learn](https://github.com/scikit-learn/scikit-learn) from 1.1.2 to 1.5.0. Release notes Sourced from scikit-learn's releases. Scikit-learn 1.5.0 We're happy to announce the 1.5.0 release. You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html and...

dependabot[bot]

mVenetos97

Issues with sbt ci-release. Investigating using sbt-sonatype plugin instead

mVenetos97

Recent Java versions seem to be incompatible with lolo but maximum versions aren't stated in the docs. I don't know what the limiting versions are but I've confirmed the following....

kyledmiller