{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hierarchical Clustering:\n",
    "* Agglomerative: Bottom-up approach. Initially, each point is a cluster, then merged later.\n",
    "* Divisive: Top-bottom approach. Initially, there is only one cluster, then separated later.\n",
    "#### Agglomertive Clustering<br>\n",
    "* Make each point a single cluster\n",
    "* Take two closest points and merge them in one cluster.\n",
    "* Repeat step 2 till only one cluster left.\n",
    "* While choosing the closest points, there are multiple ways to g <p>\n",
    "\n",
    "Take the distance of two closest point in clusters\n",
    "* Average distance\n",
    "* Centroid distance\n",
    "* Farthest points etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('my_machine-learning/datasets/iris.csv')\n",
    "\n",
    "X = df.iloc[:, [3, 4]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "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 scipy.cluster.hierarchy as sch\n",
    "dendrogram = sch.dendrogram(sch.linkage(X, method='ward')) # The ward method tries to minimise the variance in each cluster\n",
    "plt.title('Dendrogram')\n",
    "plt.xlabel('Flower')\n",
    "plt.ylabel('Euclidean Distance')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Here we get 3 clusters by dendrogram\n",
    "* Height in dendrogram at which two clusters are merged represents distance between two clusters in data space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import AgglomerativeClustering\n",
    "\n",
    "hc = AgglomerativeClustering(n_clusters=3, affinity='euclidean', linkage='ward')\n",
    "y_hc = hc.fit_predict(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The decision of merging two clusters is taken on the basis of closeness of these clusters.\n",
    "* Euclidean distance: ||a-b||^2 = √(Σ(ai-bi))\n",
    "* Squared Euclidean distance: ||a-b||^2 = Σ((ai-bi)^2)\n",
    "* Manhattan distance: ||a-b|| = Σ|ai-bi|\n",
    "* Maximum distance:||a-b||INFINITY = maxi|ai-bi|"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8, 6))\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y_hc, s=50, cmap='viridis')\n",
    "\n",
    "plt.title('Clusters using HC')\n",
    "plt.ylabel('Petal Width')\n",
    "plt.xlabel('Petal Lenght')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns = ['Species']\n",
    "\n",
    "def encoder(df):\n",
    "    for col in columns:\n",
    "        label_encoder = LabelEncoder()\n",
    "        label_encoder.fit(df[col])\n",
    "        df[col] = label_encoder.transform(df[col])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = encoder(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(15,6))\n",
    "plt.subplot(121)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y_hc, s=50, cmap='viridis')\n",
    "plt.title('Clusters using hierarchical method')\n",
    "plt.ylabel('Petal Width')\n",
    "plt.xlabel('Petal Lenght')\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.scatter(X[:, 0], X[:, 1], c=df.iloc[:,5].values, s=50, cmap='prism')\n",
    "plt.title('Original Data')\n",
    "plt.ylabel('Petal Width')\n",
    "plt.xlabel('Petal Lenght')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Disadvantage\n",
    "\n",
    "* HC is computionally expensive O(N^2Log(N)) hence is not recommended on huge datasets whereas k means using linear time\n",
    "* Sensitive to noise and outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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": "3.6.7"
  }
 },
 "nbformat": 4,
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