【报错信息】sklearn.datasets 中load

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报错信息如:

--------------------------------------------------------------------------- ImportError Traceback (most recent call last) c:\Users\32658\Desktop\mathmode\数学建模代码\回归\boston.ipynb 单元格 3 line 1 ----> 1 from sklearn.datasets import load_boston 2 boston = load_boston() File c:\Users\32658\AppData\Local\Programs\Python\Python311\Lib\site-packages\sklearn\datasets_init_.py:157, in getattr(name) 108 if name == “load_boston”: 109 msg = textwrap.dedent(“”" 110 load_boston has been removed from scikit-learn since version 1.2. 111 (…) 155 https://www.researchgate.net/publication/4974606_Hedonic_housing_prices_and_the_demand_for_clean_air 156 “”") --> 157 raise ImportError(msg) 158 try: 159 return globals()[name] ImportError: load_boston has been removed from scikit-learn since version 1.2. The Boston housing prices dataset has an ethical problem: as investigated in [1], the authors of this dataset engineered a non-invertible variable “B” assuming that racial self-segregation had a positive impact on house prices [2]. Furthermore the goal of the…
[2] Harrison Jr, David, and Daniel L. Rubinfeld. “Hedonic housing prices and the demand for clean air.” Journal of environmental economics and management 5.1 (1978): 81-102. https://www.researchgate.net/publication/4974606_Hedonic_housing_prices_and_the_demand_for_clean_air
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load_boston已经被取消掉，

解决方案

换新的数据集，其实大差不差。

from sklearn.datasets import fetch_california_housing
california = fetch_california_housing()

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官方详细解决

"""
            `load_boston` has been removed from scikit-learn since version 1.2.

            The Boston housing prices dataset has an ethical problem: as
            investigated in [1], the authors of this dataset engineered a
            non-invertible variable "B" assuming that racial self-segregation had a
            positive impact on house prices [2]. Furthermore the goal of the
            research that led to the creation of this dataset was to study the
            impact of air quality but it did not give adequate demonstration of the
            validity of this assumption.

            The scikit-learn maintainers therefore strongly discourage the use of
            this dataset unless the purpose of the code is to study and educate
            about ethical issues in data science and machine learning.

            In this special case, you can fetch the dataset from the original
            source::

                import pandas as pd
                import numpy as np

                data_url = "http://lib.stat.cmu.edu/datasets/boston"
                raw_df = pd.read_csv(data_url, sep="\\s+", skiprows=22, header=None)
                data = np.hstack([raw_df.values[::2, :], raw_df.values[1::2, :2]])
                target = raw_df.values[1::2, 2]

            Alternative datasets include the California housing dataset and the
            Ames housing dataset. You can load the datasets as follows::

                from sklearn.datasets import fetch_california_housing
                housing = fetch_california_housing()

            for the California housing dataset and::

                from sklearn.datasets import fetch_openml
                housing = fetch_openml(name="house_prices", as_frame=True)

            for the Ames housing dataset.

            [1] M Carlisle.
            "Racist data destruction?"
            <https://medium.com/@docintangible/racist-data-destruction-113e3eff54a8>

            [2] Harrison Jr, David, and Daniel L. Rubinfeld.
            "Hedonic housing prices and the demand for clean air."
            Journal of environmental economics and management 5.1 (1978): 81-102.
            <https://www.researchgate.net/publication/4974606_Hedonic_housing_prices_and_the_demand_for_clean_air>
            """

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