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TESTfbbb503804sklearn.preprocessing._encoders.OrdinalEncoder

TESTfbbb503804sklearn.preprocessing._encoders.OrdinalEncoder

Visibility: public Uploaded 17-10-2024 by Continuous Integration sklearn==0.23.1 numpy>=1.13.3 scipy>=0.19.1 joblib>=0.11 threadpoolctl>=2.0.0 0 runs
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  • openml-python python scikit-learn sklearn sklearn_0.23.1
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Encode categorical features as an integer array. The input to this transformer should be an array-like of integers or strings, denoting the values taken on by categorical (discrete) features. The features are converted to ordinal integers. This results in a single column of integers (0 to n_categories - 1) per feature.

Parameters

categoriesCategories (unique values) per feature: - 'auto' : Determine categories automatically from the training data - list : ``categories[i]`` holds the categories expected in the ith column. The passed categories should not mix strings and numeric values, and should be sorted in case of numeric values The used categories can be found in the ``categories_`` attributedefault: [[0, 1], [0, 1]]
dtypeDesired dtype of output.default: {"oml-python:serialized_object": "type", "value": "np.float64"}

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