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Feat(models): Implemented three models for license similarity #69
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atarashi/agents/models/train.py
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def model_train(): | ||
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data = pd.read_csv("atarashi/data/licenses/licenseList.csv") |
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As a future improvement, SPDX license data can be pulled in using atarashi.license.licenseDownloader.LicenseDownloader.download_license
and merged with main list using atarashi.license.license_merger.license_merger
.
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Few more changes are required. And please squash your commits.
…ween licenses #New changes update
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Agent looks good.
Tested with pip install .
Description
Implementation of Logistic Regression, Multinomial Naive Bayes and Linear SVC on license dataset licenseList.csv. The main purpose of implementing this idea was to plan for a model which can make atarashi faster and more accurate.
Files
How to use?
Test the models
atarashi -a lr_classifier path/to/file
(Logistic Regression)atarashi -a nb_classifier path/to/file
(Multinomial Naive Bayes)atarashi -a svc_classifier path/to/file
(Linear SVC)Train the models (Optional)
python3 atarashi/agents/models/train.py
ToDo
Test working and accuracy of the algorithms using
evaluator.py
proper integration with
atarashii.py
Accuracy Score
Future Scope
CC: @hastagAB @GMishx @ag4ums
Signed off by: Kaushlendra Pratap Singh [email protected]