Implementation:Scikit learn Scikit learn FetchCaliforniaHousing

Knowledge Sources	Scikit_learn Scikit-learn Docs
Domains	Machine Learning, Data Loading
Last Updated	2026-02-08 15:00 GMT

Overview

Concrete tool for fetching and loading the California housing dataset for regression tasks, provided by scikit-learn.

Description

The fetch_california_housing function downloads and caches the California housing dataset, which contains 20,640 observations on 9 variables including median house value as the target and features such as average income, housing average age, average rooms, population, latitude, and longitude. The dataset originates from Pace and Barry (1997).

Usage

Use this function when you need a real-world regression dataset for benchmarking or prototyping regression models. It is commonly used as a standard regression benchmark in scikit-learn tutorials and examples.

Code Reference

Source Location

• Repository: scikit-learn
• File: sklearn/datasets/_california_housing.py

Signature

@validate_params(...)
def fetch_california_housing(
    *,
    data_home=None,
    download_if_missing=True,
    return_X_y=False,
    as_frame=False,
    n_retries=3,
    delay=1.0,
):

Import

from sklearn.datasets import fetch_california_housing

I/O Contract

Inputs

Name	Type	Required	Description
data_home	str, PathLike or None	No	Custom directory for caching (default None uses sklearn data home)
download_if_missing	bool	No	If True, download data if not cached (default True)
return_X_y	bool	No	If True, return (data, target) instead of Bunch (default False)
as_frame	bool	No	If True, return data as pandas DataFrame (default False)
n_retries	int	No	Number of download retries (default 3)
delay	float	No	Delay between retries in seconds (default 1.0)

Outputs

Name	Type	Description
dataset	Bunch	Dictionary-like object with data, target, feature_names, DESCR, and frame
(X, y)	tuple of ndarray	Feature matrix and target array when return_X_y=True

Usage Examples

Basic Usage

from sklearn.datasets import fetch_california_housing

data = fetch_california_housing()
print(data.data.shape)    # (20640, 8)
print(data.target.shape)  # (20640,)
print(data.feature_names)

# As X, y tuple
X, y = fetch_california_housing(return_X_y=True)

Related Pages

• Principle:Scikit_learn_Scikit_learn_Dataset_Loading