https://github.com/ghazaleze/investigate_classifiers
The point is to investigate three types of classifiers (linear classifier with feature selection, linear classifier without feature selection, and a non-linear classifier) in a setting where precision and interpretability may matter.
https://github.com/ghazaleze/investigate_classifiers
feature-selection l2-regularization large-scale lasso-regression machine-learning random-forest-classifier support-vector-machine svm-classifier
Last synced: 3 months ago
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The point is to investigate three types of classifiers (linear classifier with feature selection, linear classifier without feature selection, and a non-linear classifier) in a setting where precision and interpretability may matter.
- Host: GitHub
- URL: https://github.com/ghazaleze/investigate_classifiers
- Owner: GhazaleZe
- License: mit
- Created: 2023-10-17T15:18:22.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-10-31T15:19:15.000Z (over 1 year ago)
- Last Synced: 2025-01-05T04:17:38.354Z (5 months ago)
- Topics: feature-selection, l2-regularization, large-scale, lasso-regression, machine-learning, random-forest-classifier, support-vector-machine, svm-classifier
- Language: Jupyter Notebook
- Homepage:
- Size: 559 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Investigate_Classifiers
The point is to investigate three types of classifiers (linear classifier with feature selection, linear classifier without feature selection, and a non-linear classifier) in a setting where precision and interpretability may matter.
**All the codes for investigating classifier is in main.py.**
There is Mushroom notebook that has most of the outputs of the main.py codes.