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Project description
fseval
A Feature Selector and Feature Ranker benchmarking library. Neatly integrates with wandb and sklearn. Uses Hydra as a config parser.
Usage
pip install fseval
fseval help:
fseval --help
Now, create a wandb account and login to the CLI. We are now able to run benchmarks 💪🏻. The results will automatically be uploaded to the wandb dashboard.
Run ReliefF on Iris dataset:
fseval dataset=iris estimator@pipeline.ranker=relieff
About
Built by Jeroen Overschie as part of the Masters Thesis (Data Science and Computational Complexity track at the University of Groningen).
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