Create xgboost_classifier_custom.py #11244
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| from sklearn.tree import DecisionTreeClassifier | ||
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| class CustomXGBoostClassifier: | ||
| def __init__(self, n_estimators=100, learning_rate=0.1, max_depth=3): |
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Please provide return type hint for the function: __init__. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: n_estimators
Please provide type hint for the parameter: learning_rate
Please provide type hint for the parameter: max_depth
| self.max_depth = max_depth | ||
| self.trees = [] | ||
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| def fit(self, x, y): |
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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/xgboost_classifier_custom.py, please provide doctest for the function fit
Please provide return type hint for the function: fit. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: x
Please provide type hint for the parameter: y
Please provide descriptive name for the parameter: y
| predictions += self.learning_rate * tree_predictions | ||
| self.trees.append(tree) | ||
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| def predict(self, x): |
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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/xgboost_classifier_custom.py, please provide doctest for the function predict
Please provide return type hint for the function: predict. If the function does not return a value, please provide the type hint as: def function() -> None:
Please provide type hint for the parameter: x
Please provide descriptive name for the parameter: x
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