hierarchical_agglomerative_clustering.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "marked-frederick",
   "metadata": {},
   "source": [
    "# Hierarchical agglomerative clustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "sharing-phenomenon",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.cluster import AgglomerativeClustering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "racial-webcam",
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array([\n",
    "    [-1, 3], \n",
    "    [1, 2],\n",
    "    [0, 1],\n",
    "    [4, 0],\n",
    "    [5, 4],\n",
    "    [3, 2]\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "revolutionary-increase",
   "metadata": {},
   "outputs": [],
   "source": [
    "clustering = AgglomerativeClustering(n_clusters=3, affinity='euclidean', linkage='single').fit(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "negative-stability",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, 2, 1, 0])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clustering.labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "linear-increase",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x7fd29c2b7b90>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "labels = clustering.labels_\n",
    "plt.scatter(X[labels==0, 0], X[labels==0, 1], s=50, marker='o', color='red')\n",
    "plt.scatter(X[labels==1, 0], X[labels==1, 1], s=50, marker='o', color='blue')\n",
    "plt.scatter(X[labels==2, 0], X[labels==2, 1], s=50, marker='o', color='green')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "proof-competition",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}