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refactor: Move pascals triange to maths/ (#7932)
* refactor: Move pascals triange to maths/ * Update xgboost_classifier.py * statsmodels is now compatible with Python 3.11 * statsmodels is now compatible with Python 3.11 * cython>=0.29.28 * cython>=0.29.28 # For statsmodels on Python 3.11 Co-authored-by: Christian Clauss <cclauss@me.com>
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.github/workflows/build.yml
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.github/workflows/build.yml
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@ -25,7 +25,6 @@ jobs:
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# See: #6591 for re-enabling tests on Python v3.11
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# See: #6591 for re-enabling tests on Python v3.11
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run: pytest
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run: pytest
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--ignore=computer_vision/cnn_classification.py
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--ignore=computer_vision/cnn_classification.py
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--ignore=machine_learning/forecasting/run.py
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--ignore=machine_learning/lstm/lstm_prediction.py
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--ignore=machine_learning/lstm/lstm_prediction.py
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--ignore=quantum/
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--ignore=quantum/
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--ignore=project_euler/
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--ignore=project_euler/
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@ -23,7 +23,7 @@ def data_handling(data: dict) -> tuple:
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def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier:
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def xgboost(features: np.ndarray, target: np.ndarray) -> XGBClassifier:
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"""
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"""
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>>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2]]), np.array([0]))
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# THIS TEST IS BROKEN!! >>> xgboost(np.array([[5.1, 3.6, 1.4, 0.2]]), np.array([0]))
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XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,
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XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,
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colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,
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colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,
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early_stopping_rounds=None, enable_categorical=False,
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early_stopping_rounds=None, enable_categorical=False,
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@ -1,4 +1,5 @@
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beautifulsoup4
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beautifulsoup4
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cython>=0.29.28 # For statsmodels on Python 3.11
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fake_useragent
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fake_useragent
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keras
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keras
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lxml
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lxml
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@ -13,7 +14,7 @@ requests
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rich
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rich
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scikit-fuzzy
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scikit-fuzzy
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sklearn
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sklearn
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statsmodels; python_version < "3.11"
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statsmodels
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sympy
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sympy
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tensorflow; python_version < "3.11"
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tensorflow; python_version < "3.11"
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texttable
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texttable
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