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A machine learning pipeline to help facilitate faster feature engineering, feature selection, model fitting, and model evaluation

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Machine-Learning-Pipeline

The Pipeline Class is stored in the folder @Pipeline and consists of the functions: loadData.m, featureEngineering.m, featureSelection.m, fit.m, and evaluate.m. An example of how to use the Pipeline on publically available data from Severson et. al is given in RunPipeline.m.

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A machine learning pipeline to help facilitate faster feature engineering, feature selection, model fitting, and model evaluation

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