An rigorous, well documented machine learning analysis pipeline for binary classification datasets assembled as parallelizable command line modules. Includes exploratory analysis, data processing, feature processing, ML modeling (11 algorithms) with hyperparameter sweeps, visualizations, and statistical analysis. A comprehensive starting point to adapt to your own dataset. Testing changes
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An rigorous, machine learning analysis pipeline for binary classification datasets assembled as parallelizable command line modules. Includes exploratory analysis, data processing, feature processing, ML modeling (11 algorithms) with hyperparameter sweeps, visualizations, and statistical analysis. A comprehensive starting point to adapt to your …
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UrbsLab/scikit_ML_Pipeline_Binary_Parallel
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An rigorous, machine learning analysis pipeline for binary classification datasets assembled as parallelizable command line modules. Includes exploratory analysis, data processing, feature processing, ML modeling (11 algorithms) with hyperparameter sweeps, visualizations, and statistical analysis. A comprehensive starting point to adapt to your …
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