Hello there, Today I tagged mlpack 3.2.0 and released it. It didn't contain quite everything that we discussed at the last mlpack video meeting, but it has most of it, and as the few final PRs get merged, we can easily release patch updates.
You can download the code at https://www.mlpack.org/files/mlpack-3.2.0.tar.gz and you can find the documentation updated on the website at https://www.mlpack.org/. The Windows installer for 3.2.0 isn't finished building yet, but when it is, I'll update the homepage link. Here is a changelog: ----- * Fix occasionally-failing RADICAL test (#1924). * Fix gcc 9 OpenMP compilation issue (#1970). * Added support for loading and saving of images (#1903). * Add Multiple Pole Balancing Environment (#1901, #1951). * Added functionality for scaling of data (#1876); see the command-line binding `mlpack_preprocess_scale` or Python binding `preprocess_scale()`. * Add new parameter `maximum_depth` to decision tree and random forest bindings (#1916). * Fix prediction output of softmax regression when test set accuracy is calculated (#1922). * Pendulum environment now checks for termination. All RL environments now have an option to terminate after a set number of time steps (no limit by default) (#1941). * Add support for probabilistic KDE (kernel density estimation) error bounds when using the Gaussian kernel (#1934). * Fix negative distances for cover tree computation (#1979). * Fix cover tree building when all pairwise distances are 0 (#1986). * Improve KDE pruning by reclaiming not used error tolerance (#1954, #1984). * Optimizations for sparse matrix accesses in z-score normalization for CF (#1989). * Add `kmeans_max_iterations` option to GMM training binding `gmm_train_main`. * Bump minimum Armadillo version to 8.400.0 due to ensmallen dependency requirement (#2015). ----- This release is the result of the hard work of everyone, and it contains a lot of code that was written as part of GSoC this year. Awesome work everyone! There is some really cool support in here and I hope that you find it useful. :) If you're using mlpack and you find bugs, performance issues, regressions, or just have some feature requests (or even want to contribute), please let us know! You can send an email to this list, you can post an issue on Github, or you can chat in IRC. See http://mlpack.org/community.html for more information. Have a great day! Ryan -- Ryan Curtin | "Maybe the next time." [email protected] | - J.G. Ballard _______________________________________________ mlpack mailing list [email protected] http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
