Re: [scikit-learn] Retracting model from the 'blackbox' SVM (Sebastian Raschka)

Hi Sebastian, If you are looking to reduce the feature space for your model, I suggest you look at the scikit-learn page on doing just that http://scikit-learn.org/stable/modules/feature_selection.html David On 2018-05-04 12:00 PM, scikit-learn-requ...@python.org wrote: Send scikit-learn

[scikit-learn] pipeline for modifying target and number of samples

the sklearn tools, and integrates with all the sklearn transformers and estimators. It also has some new options for setting hyper-parameters with callables and in reference to other parameters. The implementation is in my time series package seglearn: https://github.com/dmbee/seglearn - Best David

[scikit-learn] seglearn: package for time series and sequence learning

for those of you interested in this area. https://github.com/dmbee/seglearn Cheers, David Burns ___ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn

Re: [scikit-learn] New Transformer (Guillaume Lema?tre)

at scikit-learn-ow...@python.org When replying, please edit your Subject line so it is more specific than "Re: Contents of scikit-learn digest..." Today's Topics: 1. New Transformer (David Burns) 2. Re: New Transformer (Guillaume Lema?tre) 3. Re: New Transformer (Man

Re: [scikit-learn] Inclusion of an LSTM Classifier

There is an sklearn wrapper for Keras models in the Keras library. That's an easy way to use LSTM in sklearn. Also the sklearn estimator API is pretty easy to figure out if you want to roll your own wrapper for any model really. ___ scikit-learn mailing