sklearn.datasets.load_boston

sklearn.datasets.load_boston(return_X_y=False)

Load and return the boston house-prices dataset (regression).

Samples total	506
Dimensionality	13
Features	real, positive
Targets	real 5. - 50.

Parameters:

return_X_y : boolean, default=False.

If True, returns (data, target) instead of a Bunch object. See below for more information about the data and target object.

New in version 0.18.

Returns:

data : Bunch

Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘target’, the regression targets, and ‘DESCR’, the full description of the dataset.

(data, target) : tuple if return_X_y is True

New in version 0.18.

Examples

>>> from sklearn.datasets import load_boston
>>> boston = load_boston()
>>> print(boston.data.shape)
(506, 13)

Examples using sklearn.datasets.load_boston

Imputing missing values before building an estimator

Plotting Cross-Validated Predictions

Model Complexity Influence

Outlier detection on a real data set

Gradient Boosting regression

Feature selection using SelectFromModel and LassoCV