XGBoost Classifier #7106
XGBoost Classifier #7106
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@cclauss Can you please review this I hope this will be merged as all the tests are passing. |
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Your only function, https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md#what-is-an-algorithm What is an Algorithm?An Algorithm is one or more functions (or classes) that:
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But there are algorithms which already exists in your repo that do not return output. The output is the graph it plots. The algorithm does takes input at line 28 for training. It's a machine learning algorithm. |
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Why not open a pull request here? https://github.com/dmlc/xgboost/tree/master/demo They probably want how-to-use examples. We want to focus on algorithms. |
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This algorithm does not have any functions at all but it is there in this repository. |
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Yes. That was merged 1,196 days ago and we have raised our standards for new submissions significantly since then. There are lots of repos that are easier to contribute to. |
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| return classifier | ||
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| def main() -> None: |
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As there is no test file in this pull request nor any test function or class in the file machine_learning/xgboostclassifier.py, please provide doctest for the function main
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| return classifier | ||
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| def main() -> None: |
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As there is no test file in this pull request nor any test function or class in the file machine_learning/xgboostclassifier.py, please provide doctest for the function main
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OK. I have added better names and wrapped long lines to placate pre-commit. The only test that fails is one that I do not know how to solve. Please click the UNEXPECTED EXCEPTION: ValueError('Invalid classes inferred from unique values of |
algorithms-keeper
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Thank you very much. That's so kind of you. |
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| def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier: | ||
| """ | ||
| >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2],[4.6, 3.4, 1.4, 0.7]]), np.array([1,2])) |
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| >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2],[4.6, 3.4, 1.4, 0.7]]), np.array([1,2])) | |
| >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2],[4.6, 3.4, 1.4, 0.7]]), np.array([0, 1])) |
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Thank You very much. I am looking into this. In google collab it's saying all test passed but here it is showing error. I will get into this and fix it.
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algorithms-keeper
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removed
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tests are failing
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@cclauss Thank you with your help I removed the errors. |
cclauss
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hacktoberfest
hacktoberfest-accepted
Thank you for your guidance and help. |
Describe your change:
Checklist:
Fixes: #{$ISSUE_NO}.