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TEST2dec9b986csklearn.preprocessing._data.StandardScaler

Visibility: public Uploaded 10-01-2024 by Continuous Integration
sklearn==1.3.2
numpy>=1.17.3
scipy>=1.5.0
joblib>=1.1.1
threadpoolctl>=2.0.0 0 runs

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copy | If False, try to avoid a copy and do inplace scaling instead This is not guaranteed to always work inplace; e.g. if the data is not a NumPy array or scipy.sparse CSR matrix, a copy may still be returned | default: true |

with_mean | If True, center the data before scaling This does not work (and will raise an exception) when attempted on sparse matrices, because centering them entails building a dense matrix which in common use cases is likely to be too large to fit in memory | default: false |

with_std | If True, scale the data to unit variance (or equivalently, unit standard deviation). | default: true |

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