sklearn.datasets.load_breast_cancer¶

sklearn.datasets.load_breast_cancer(return_X_y=False)[source]¶

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

Read more in the User Guide.

Parameters

return_X_yboolean, 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

dataBunch

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, ‘filename’, the physical location of breast cancer csv dataset (added in version 0.20).

(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

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']

Examples using sklearn.datasets.load_breast_cancer¶

Post pruning decision trees with cost complexity pruning¶

Permutation Importance with Multicollinear or Correlated Features¶