sklearn.datasets.load_diabetes

sklearn.datasets.load_diabetes(return_X_y=False)

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, ‘target’, the regression target for each sample, ‘data_filename’, the physical location of diabetes data csv dataset, and ‘target_filename’, the physical location of diabetes targets csv datataset (added in version 0.20).

(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

Imputing missing values before building an estimator

Lasso path using LARS

Linear Regression Example

Sparsity Example: Fitting only features 1 and 2

Lasso and Elastic Net

Lasso model selection: Cross-Validation / AIC / BIC