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@victorromeo
Last active January 8, 2021 11:46
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2D Means Shift.ipynb
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "2D Means Shift.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyOW1gelir0v6ChJpYfwV64m",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/gist/victorromeo/2c1548f9fd2a16534af13ddd55d8dc91/untitled2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 298
},
"id": "ihiJpU6yxmqt",
"outputId": "aaf8f858-91a7-4151-ad97-08a05693a1a1"
},
"source": [
"import numpy as np\n",
"from sklearn.cluster import MeanShift, estimate_bandwidth\n",
"from sklearn.datasets import make_blobs\n",
"\n",
"# #############################################################################\n",
"# Generate sample data\n",
"centers = [[1, 1], [-1, -1], [1, -1]]\n",
"X, _ = make_blobs(n_samples=10000, centers=centers, cluster_std=0.6)\n",
"\n",
"# #############################################################################\n",
"# Compute clustering with MeanShift\n",
"\n",
"# The following bandwidth can be automatically detected using\n",
"bandwidth = estimate_bandwidth(X, quantile=0.2, n_samples=500)\n",
"\n",
"ms = MeanShift(bandwidth=bandwidth, bin_seeding=True)\n",
"ms.fit(X)\n",
"labels = ms.labels_\n",
"cluster_centers = ms.cluster_centers_\n",
"\n",
"labels_unique = np.unique(labels)\n",
"n_clusters_ = len(labels_unique)\n",
"\n",
"print(\"number of estimated clusters : %d\" % n_clusters_)\n",
"\n",
"# #############################################################################\n",
"# Plot result\n",
"import matplotlib.pyplot as plt\n",
"from itertools import cycle\n",
"\n",
"plt.figure(1)\n",
"plt.clf()\n",
"\n",
"colors = cycle('bgrcmykbgrcmykbgrcmykbgrcmyk')\n",
"for k, col in zip(range(n_clusters_), colors):\n",
" my_members = labels == k\n",
" cluster_center = cluster_centers[k]\n",
" plt.plot(X[my_members, 0], X[my_members, 1], col + '.')\n",
" plt.plot(cluster_center[0], cluster_center[1], 'o', markerfacecolor=col,\n",
" markeredgecolor='k', markersize=14)\n",
"plt.title('Estimated number of clusters: %d' % n_clusters_)\n",
"plt.show()"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"number of estimated clusters : 3\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
}
]
}
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