plot_silhouette#

scikitplot.api.metrics.plot_silhouette(X, cluster_labels, *, metric='euclidean', copy=True, title='Silhouette Analysis', ax=None, fig=None, figsize=None, title_fontsize='large', text_fontsize='medium', cmap=None, digits=4, **kwargs)[source]#

Plots silhouette analysis of clusters provided.

Silhouette analysis is a method of interpreting and validating the consistency within clusters of data. It measures how similar an object is to its own cluster compared to other clusters.

Parameters:
Xarray-like, shape (n_samples, n_features)

Data to cluster, where n_samples is the number of samples and n_features is the number of features.

cluster_labelsarray-like, shape (n_samples,)

Cluster label for each sample.

metricstr or callable, optional, default=’euclidean’

The metric to use when calculating distance between instances in a feature array. If metric is a string, it must be one of the options allowed by sklearn.metrics.pairwise.pairwise_distances. If X is the distance array itself, use “precomputed” as the metric.

copybool, optional, default=True

Determines whether fit is used on clf or on a copy of clf.

titlestr, optional, default=’Silhouette Analysis’

Title of the generated plot.

axlist of matplotlib.axes.Axes, optional, default=None

The axis to plot the figure on. If None is passed in the current axes will be used (or generated if required). Axes like fig.add_subplot(1, 1, 1) or plt.gca()

figmatplotlib.pyplot.figure, optional, default: None

The figure to plot the Visualizer on. If None is passed in the current plot will be used (or generated if required).

Added in version 0.3.9.

figsizetuple of int, optional, default=None

Size of the figure (width, height) in inches.

title_fontsizestr or int, optional, default=’large’

Font size for the plot title.

text_fontsizestr or int, optional, default=’medium’

Font size for the text in the plot.

cmapNone, str or matplotlib.colors.Colormap, optional, default=None

Colormap used for plotting. Options include ‘viridis’, ‘PiYG’, ‘plasma’, ‘inferno’, ‘nipy_spectral’, etc. See Matplotlib Colormap documentation for available choices.

digitsint, optional, default=4

Number of digits for formatting output floating point values.

Added in version 0.3.9.

Returns:
matplotlib.axes.Axes

The axes on which the plot was drawn.

References * “scikit-learn silhouette_score”.#

Examples

>>> from sklearn.cluster import KMeans
>>> from sklearn.datasets import load_iris as data_3_classes
>>> import scikitplot as skplt
>>> X, y = data_3_classes(return_X_y=True, as_frame=False)
>>> kmeans = KMeans(n_clusters=3, random_state=0)
>>> cluster_labels = kmeans.fit_predict(X)
>>> skplt.metrics.plot_silhouette(
>>>     X,
>>>     cluster_labels,
>>> );

(Source code, png)

Silhouette Plot