I've been following the progress and this is really beginning to look pretty awesome!
-viral On Friday, June 10, 2016 at 7:29:39 AM UTC-4, Cedric St-Jean wrote: > > I'm pleased to announce the first major relase of ScikitLearn.jl > <https://github.com/cstjean/ScikitLearn.jl>! It now works with the > following Julia models: > > *DecisionTree.jl > <https://github.com/bensadeghi/DecisionTree.jl#scikitlearnjl>* > - DecisionTreeClassifier > - DecisionTreeRegressor > - RandomForestClassifier > - RandomForestRegressor > - AdaBoostStumpClassifier > > *LowRankModels.jl > <https://github.com/madeleineudell/LowRankModels.jl#scikitlearn>* > - SkGLRM: Generalized Low Rank Models > - PCA: Principal Component Analysis > - QPCA: Quadratically Regularized PCA > - RPCA: Robust PCA > - NNMF: Non-negative matrix factorization > - K-Means > > *GaussianProcesses.jl* <https://github.com/STOR-i/GaussianProcesses.jl> > > *GaussianMixtures.jl* <https://github.com/davidavdav/GaussianMixtures.jl> > > Full list here <http://scikitlearnjl.readthedocs.io/en/latest/models/>. > Special > thanks to *@BenSadeghi*, *@davidavdav*, *@fairbrot *and *@madeleineudell *for > their help and support. > > DataFrames <https://github.com/JuliaStats/DataFrames.jl> are now accepted > as inputs, through DataFrameMapper > <http://scikitlearnjl.readthedocs.io/en/latest/dataframes/>. And finally, > the Python version of scikit-learn has been made an optional dependency, > meaning that it's now possible to run a cross-validated grid-search of an > NNMF and DecisionTreeClassifier pipeline, in 100% Julia. Though, of course, > all of the 150 Python models > <http://scikitlearnjl.readthedocs.io/en/latest/models/> remain accessible. > > If you're a package maintainer and would like to support the scikit-learn > interface, it's easy <https://github.com/cstjean/ScikitLearnBase.jl>, and > I'm glad to help, just get in touch > <https://github.com/cstjean/ScikitLearn.jl/issues> if you have any > questions. > > Cédric >
