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Added More Hyperparameters and added VotingRegressor #121
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Ensure the PR matches the requirements mentioned in the Contribution guide. The maintainer might get in touch to enusre quality. Thanks for your time
Hey @agnij-dutta please mention the issue # |
issue reference [issue #129 ] |
@agnij-dutta Please link the issue using keywords. (fixes/closes..) You can find the detailed info about the same here: If needed please refer to the closed PRs that were merged. Thanks & regards |
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Ensure the PR matches the requirements mentioned in the Contribution guide. The maintainer might get in touch to enusre quality. Thanks for your time
@agnij-dutta , kindly edit your main comment, i.e. the first one and mention the issue number in it |
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@agnij-dutta Please link the issue using keywords. (fixes/closes..) You can find the detailed info about the same here:
https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue#linking-a-pull-request-to-an-issue-using-a-keyword
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@agnij-dutta Please quantify your claims. Please add the old vs new accuracy and other evaluation metrics that you have changed.
Maybe you can them in the description of the PR itself.
Thanks and regards
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@agnij-dutta Closing this PR due to long period of inactivity. Please feel free to reopen if needed.
Thanks,
Mayuresh
Fixes issue #129
Description of changes:
Added a polynomial feature transformer to create new features for improving model performance.
Introduced a voting regressor that combines multiple model predictions for more accurate results.
Performed hyperparameter tuning for the voting regressor using GridSearchCV, optimizing the weights parameter.
Calculated additional evaluation metrics (accuracy, precision, recall, F1 score, confusion matrix) to provide a comprehensive view of model performance.
Fixed an error by removing the invalid voting parameter in the GridSearchCV call.
Benefits:
Enhanced model accuracy and recall.
More comprehensive evaluation metrics.
Improved hyperparameter tuning process.