https://github.com/urbslab/scikit_ml_pipeline_binary_parallel

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 own dataset.
https://github.com/urbslab/scikit_ml_pipeline_binary_parallel

Last synced: 12 months ago
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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 own dataset.

• Host: GitHub
• URL: https://github.com/urbslab/scikit_ml_pipeline_binary_parallel
• Owner: UrbsLab
• License: gpl-3.0
• Created: 2020-05-19T00:07:29.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2021-04-23T00:13:10.000Z (about 5 years ago)
• Last Synced: 2023-12-15T04:05:27.394Z (over 2 years ago)
• Language: Python
• Homepage:
• Size: 257 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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# scikit_ML_Pipeline_Binary_Parallel

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.

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