Python package for Bayesian Machine Learning with scikit-learn API Installing & Upgrading package pip install https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip pip install –upgrade https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip Algorithms ARD Models Relevance Vector Regression (version 2.0) code, tutorial Relevance Vector Classifier (version 2.0) code, tutorial Type II Maximum Likelihood ARD Linear Regression code Type II Maximum Likelihood ARD Logistic Regression code, tutorial Variational Relevance Vector Regression

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py_neuromodulation The py_neuromodulation toolbox allows for real time capable processing of multimodal electrophysiological data. The primary use is movement prediction for adaptive deep brain stimulation. Find the documentation here https://neuromodulation.github.io/py_neuromodulation/ for example usage and parametrization. Setup For running this toolbox first create a new virtual conda environment: conda env create –file=env.yml –user The main modules include running real time enabled feature preprocessing based on iEEG BIDS data. Different features can be enabled/disabled and parametrized in the `https://github.com/neuromodulation/py_neuromodulation/blob/main/pyneuromodulation/nm_settings.json>`_. The current implementation […]