sklearn.datasets.load_digits¶
- sklearn.datasets.load_digits(n_class=10)[source]¶
Load and return the digits dataset (classification).
Each datapoint is a 8x8 image of a digit.
Classes 10 Samples per class ~180 Samples total 1797 Dimensionality 64 Features integers 0-16 Read more in the User Guide.
Parameters: n_class : integer, between 0 and 10, optional (default=10)
The number of classes to return.
Returns: data : Bunch
Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘images’, the images corresponding to each sample, ‘target’, the classification labels for each sample, ‘target_names’, the meaning of the labels, and ‘DESCR’, the full description of the dataset.
Examples
To load the data and visualize the images:
>>> from sklearn.datasets import load_digits >>> digits = load_digits() >>> print(digits.data.shape) (1797, 64) >>> import pylab as pl >>> pl.gray() >>> pl.matshow(digits.images[0]) >>> pl.show()
