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

Yes, that's correct. The `load_boston` dataset has been removed from scikit-learn since version 1.2. This was due to the fact that the dataset is now widely available from other sources, such as the UCI Machine Learning Repository. In addition, scikit-learn now focuses more on machine learning algorithms and tools, rather than datasets. However, users can still access the `load_boston` dataset through other means, such as loading it from the UCI repository or using other libraries.

相关问题

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

您提到的是对的，`load_boston`函数确实不再直接存在于scikit-learn的最新版本中，比如从1.2及以后的版本。这个变化的原因可能是为了简化库的结构和减少依赖，或者是为了鼓励用户直接访问更广泛的数据源，如`pandas`库中的数据。

如果你想继续使用波士顿房价数据集，可以采取以下几种方式：

1. **通过pandas加载**：可以从UCI Machine Learning Repository或其他数据存储库下载CSV文件，然后使用`pandas`读取：

import pandas as pd
url = "https://archive.ics.uci.edu/ml/machine-learning-databases/housing/housing.data"
column_names = ['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD', 'TAX', 'PTRATIO', 'B', 'LSTAT', 'MEDV']
boston_df = pd.read_csv(url, header=None, names=column_names)

2. **使用fetch_california_housing**：虽然不是原生的波士顿数据集，但它是相似的加利福尼亚州住房数据，可以在scikit-learn中找到：

from sklearn.datasets import fetch_california_housing
california_housing = fetch_california_housing()

3. **利用其他的机器学习库**：像`seaborn`或`statsmodels`库也可能提供类似数据集。

请注意，无论采用哪种方法，你都需要自行处理数据预处理工作，包括编码分类变量、填充缺失值（如果有的话）、标准化等。

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

0. What package should I use instead to load the Boston dataset in scikit-learn?

You can use the `fetch_openml` function from scikit-learn to load the Boston dataset, as follows:

from sklearn.datasets import fetch_openml

boston = fetch_openml(name='boston')

This will load the Boston dataset into a dictionary-like object, where you can access the feature names and data as follows:

print(boston.feature_names)
print(boston.data)

I hope this helps!