sklearn.datasets.load_diabetes()

sklearn.datasets.load_diabetes

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

Load and return the diabetes dataset (regression).

Samples total	442
Dimensionality	10
Features	real, -.2 < x < .2
Targets	integer 25 - 346

Read more in the User Guide.

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 and ‘target’, the regression target for each sample. (data, target) : tuple if return_X_y is True New in version 0.18.

Examples using sklearn.datasets.load_diabetes

Cross-validation on diabetes Dataset Exercise

Lasso and Elastic Net

Lasso path using LARS

Lasso model selection: Cross-Validation / AIC / BIC

Linear Regression Example

Sparsity Example: Fitting only features 1 and 2