Dynex Scikit-Learn Plugin
This package provides a scikit-learn transformer for feature selection using the Dynex Neuromorphic Computing Platform. It is built to integrate seamlessly with scikit-learn, an industry-standard, state-of-the-art ML library for Python. This plug-in makes it easier to use the Dynex platform for the feature selection piece of ML workflows. Feature selection – a key building block of machine learning – is the problem of determining a small set of the most representative characteristics to improve model training and performance in ML. With this new plug-in, ML developers need not be experts in optimization or hybrid solving to get the business and technical benefits of both. Developers creating feature selection applications can build a pipeline with scikit-learn and then embed the Dynex Platform into this workflow more easily and efficiently. The package’s main class, SelectFromQuadraticModel, can be used in any existing sklearn pipeline.