mvpa2.datasets.sources.skl_data.skl_breast_cancer

mvpa2.datasets.sources.skl_data.skl_breast_cancer(return_X_y=False)

Load and return the breast cancer wisconsin dataset (classification).

The breast cancer dataset is a classic and very easy binary classification dataset.

Classes	2
Samples per class	212(M),357(B)
Samples total	569
Dimensionality	30
Features	real, positive

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 classification labels, ‘target_names’, the meaning of the labels, ‘feature_names’, the meaning of the features, and ‘DESCR’, the full description of the dataset.

(data, target) : tuple if return_X_y is True

New in version 0.18.

The copy of UCI ML Breast Cancer Wisconsin (Diagnostic) dataset is

downloaded from:

https://goo.gl/U2Uwz2

Notes

This function has been auto-generated by wrapping load_breast_cancer() from the sklearn package. The documentation of this function has been kept verbatim. Consequently, the actual return value is not as described in the documentation, but the data is returned as a PyMVPA dataset.

Examples

Let’s say you are interested in the samples 10, 50, and 85, and want to know their class name.

>>> from sklearn.datasets import load_breast_cancer
>>> data = load_breast_cancer()
>>> data.target[[10, 50, 85]]
array([0, 1, 0])
>>> list(data.target_names)
['malignant', 'benign']