Home - News ( United States | United Kingdom | Italy | Germany ) - Football scores

Showing content from https://scikit-learn.org/dev/auto_examples/../modules/../auto_examples/cluster/plot_mean_shift.html below:

A demo of the mean-shift clustering algorithm — scikit-learn 1.8.dev0 documentation

Note

Go to the end to download the full example code. or to run this example in your browser via JupyterLite or Binder

Reference:

Dorin Comaniciu and Peter Meer, “Mean Shift: A robust approach toward feature space analysis”. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2002. pp. 603-619.

# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause

import numpy as np

from sklearn.cluster import MeanShift, estimate_bandwidth
from sklearn.datasets import make_blobs

centers = [[1, 1], [-1, -1], [1, -1]]
X, _ = make_blobs(n_samples=10000, centers=centers, cluster_std=0.6)

# The following bandwidth can be automatically detected using
bandwidth = estimate_bandwidth(X, quantile=0.2, n_samples=500)

ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)
ms.fit(X)
labels = ms.labels_
cluster_centers = ms.cluster_centers_

labels_unique = np.unique(labels)
n_clusters_ = len(labels_unique)

print("number of estimated clusters : %d" % n_clusters_)

number of estimated clusters : 3

import matplotlib.pyplot as plt

plt.figure(1)
plt.clf()

colors = ["#dede00", "#377eb8", "#f781bf"]
markers = ["x", "o", "^"]

for k, col in zip(range(n_clusters_), colors):
    my_members = labels == k
    cluster_center = cluster_centers[k]
    plt.plot(X[my_members, 0], X[my_members, 1], markers[k], color=col)
    plt.plot(
        cluster_center[0],
        cluster_center[1],
        markers[k],
        markerfacecolor=col,
        markeredgecolor="k",
        markersize=14,
    )
plt.title("Estimated number of clusters: %d" % n_clusters_)
plt.show()

Total running time of the script: (0 minutes 0.413 seconds)

Related examples

Gallery generated by Sphinx-Gallery

RetroSearch is an open source project built by @garambo | Open a GitHub Issue

Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo

HTML: 3.2 | Encoding: UTF-8 | Version: 0.7.4