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 thedata
andtarget
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:
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']