https://github.com/jhylin/ml1-1_small_mols_in_chembl

Polars dataframe library and logistic regression in scikit-learn (update)
https://github.com/jhylin/ml1-1_small_mols_in_chembl

logistic-regression machine-learning parquet-files polars-dataframe scikit-learn

Last synced: 26 days ago
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Polars dataframe library and logistic regression in scikit-learn (update)

• Host: GitHub
• URL: https://github.com/jhylin/ml1-1_small_mols_in_chembl
• Owner: jhylin
• Created: 2024-08-31T09:13:59.000Z (2 months ago)
• Default Branch: main
• Last Pushed: 2024-10-11T21:42:46.000Z (27 days ago)
• Last Synced: 2024-10-12T23:43:38.022Z (26 days ago)
• Topics: logistic-regression, machine-learning, parquet-files, polars-dataframe, scikit-learn
• Language: Jupyter Notebook
• Homepage:
• Size: 325 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
A series of Quarto markdown files (.qmd) are stored in this repository for an updated version of this old post on

"Small molecules in ChEMBL database - Series 1.1 - Polars dataframe library and machine learning in scikit-learn". This old post will be updated and splitted into smaller posts for ease of reading (and also to avoid draining my energy too quickly). After updating this first post of the series, I may also look at two other posts (basically series 1.2 & 1.3) to see if they can be changed as well. I'll attach .ipynb versions of each updated post when they're done.

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As on 26/9/24:

* Only really need to use either set_output(transformation="polars") or set_config(transformation="polars") once to get polars df output, configured plot of features and coefficients for ease of html viewing plus still pending checks on predicted probabilities

* ETA: hopefully within the last quarter of the year for the first lot (i.e. ML 1-1-1 to 1-1-4) at least!