sklearnモジュールのエラーについて

Question

前提

エラーを解決したいです。

エラーメッセージ

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

該当のソースコード

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

from sklearn.datasets import load_boston

Answer 1

前提
エラーを解決したいです。

とのことですが、

エラーの原因と代替方法は既にエラーメッセージに記載の通りです。
何が分からないのでしょうか？

日本語での説明が必要であれば下記などが参考になるかと思います。
機械学習の回帰データとしては、ボストン住宅価格データではなく、カリフォルニア住宅価格データを使おう