sklearn.datasets
.load_breast_cancer¶
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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 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 TrueNew 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']