plot_elbow#

scikitplot.api.estimators.plot_elbow(clf, X, *, cluster_ranges=None, show_cluster_time=True, n_jobs=1, title='Elbow Curves', title_fontsize='large', text_fontsize='medium', **kwargs)[source]#

Plot the elbow curve for different values of K in KMeans clustering.

Parameters:

clfobject: A clusterer instance with fit, fit_predict, and score methods, and an n_clusters hyperparameter. Typically an instance of sklearn.cluster.KMeans.
Xarray-like of shape (n_samples, n_features): The data to cluster, where n_samples is the number of samples and n_features is the number of features.
cluster_rangeslist of int or None, optional, default=range(1, 12, 2): List of values for n_clusters over which to plot the explained variances.
show_cluster_timebool, optional: Whether to include a plot of the time taken to cluster for each value of K.
n_jobsint, optional, default=1: The number of jobs to run in parallel.
titlestr, optional, default=”Elbow Plot”: The title of the generated plot.
title_fontsizestr or int, optional, default=”large”: Font size of the title. Accepts Matplotlib font sizes, such as “small”, “medium”, “large”, or an integer value.
text_fontsizestr or int, optional, default=”medium”: Font size of the text labels. Accepts Matplotlib font sizes, such as “small”, “medium”, “large”, or an integer value.
**kwargs: dict: Generic keyword arguments.

Returns:

axmatplotlib.axes.Axes: The axes on which the plot was drawn.

Other Parameters:

axmatplotlib.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).
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).
figsizetuple, optional, default=None: Width, height in inches. Tuple denoting figure size of the plot e.g. (12, 5)
nrowsint, optional, default=1: Number of rows in the subplot grid.
ncolsint, optional, default=1: Number of columns in the subplot grid.
plot_stylestr, optional, default=None: Check available styles with “plt.style.available”. Examples include: [‘ggplot’, ‘seaborn’, ‘bmh’, ‘classic’, ‘dark_background’, ‘fivethirtyeight’, ‘grayscale’, ‘seaborn-bright’, ‘seaborn-colorblind’, ‘seaborn-dark’, ‘seaborn-dark-palette’, ‘tableau-colorblind10’, ‘fast’].

Added in version 0.4.0.
show_figbool, default=True: Show the plot.
save_figbool, default=False: Save the plot.
save_fig_filenamestr, optional, default=’’: Specify the path and filetype to save the plot. If nothing specified, the plot will be saved as png inside result_images under to the current working directory. Defaults to plot image named to used func.__name__.
verbosebool, optional: If True, prints debugging information.

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(random_state=0)
>>> skplt.estimators.plot_elbow(
>>>     kmeans,
>>>     X,
>>>     cluster_ranges=range(1, 10),
>>> );

(Source code, png)

Gallery examples#

plot_elbow with examples

plot_elbow#

Gallery examples#

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