sklearn.datasets.load_boston()

sklearn.datasets.load_boston(return_X_y=False) [source]

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