TP4_DM.ipynb

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      "include_colab_link": true
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      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/alaeddinehamroun/Data-Mining-TP/blob/main/TP4_DM.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Partie 1 : Données de travail"
      ],
      "metadata": {
        "id": "ccqleYkSc7GR"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FUWuiQmB_qTK",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cad87310-499c-49e0-d6b2-930a62a9c988"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "         calories      sodium     calcium    lipides     retinol    folates  \\\n",
            "count   29.000000   29.000000   29.000000  29.000000   29.000000  29.000000   \n",
            "mean   300.034483  210.086207  185.734483  24.158621   67.562069  13.010345   \n",
            "std     91.914356  108.678923   72.528882   8.129642   24.163098  11.723339   \n",
            "min     70.000000   22.000000   72.600000   3.400000   37.100000   1.200000   \n",
            "25%    292.000000  140.000000  132.900000  23.400000   51.600000   4.900000   \n",
            "50%    321.000000  223.000000  202.300000  26.300000   62.300000   6.400000   \n",
            "75%    355.000000  276.000000  220.500000  29.100000   76.400000  21.100000   \n",
            "max    406.000000  432.000000  334.600000  33.300000  150.500000  36.400000   \n",
            "\n",
            "       proteines  cholesterol  magnesium  \n",
            "count  29.000000    29.000000  29.000000  \n",
            "mean   20.168966    74.586207  26.965517  \n",
            "std     6.959788    28.245755  11.318388  \n",
            "min     4.100000    10.000000  10.000000  \n",
            "25%    17.800000    70.000000  20.000000  \n",
            "50%    21.000000    80.000000  26.000000  \n",
            "75%    23.400000    90.000000  30.000000  \n",
            "max    35.700000   120.000000  51.000000  \n"
          ]
        }
      ],
      "source": [
        "import pandas as pd\n",
        "fromage=pd.read_table(r\"/content/fromage1.txt\",sep=\"\\t\",header=0,index_col=0)\n",
        "print(fromage.describe())"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(fromage)"
      ],
      "metadata": {
        "id": "wpZZzMxbBWCS",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "1f8a94fd-dad8-4b3b-ab4f-c3f3043217f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                    calories  sodium  calcium  lipides  retinol  folates  \\\n",
            "Fromages                                                                   \n",
            "CarredelEst              314   353.5     72.6     26.3     51.6     30.3   \n",
            "Babybel                  314   238.0    209.8     25.1     63.7      6.4   \n",
            "Beaufort                 401   112.0    259.4     33.3     54.9      1.2   \n",
            "Bleu                     342   336.0    211.1     28.9     37.1     27.5   \n",
            "Camembert                264   314.0    215.9     19.5    103.0     36.4   \n",
            "Cantal                   367   256.0    264.0     28.8     48.8      5.7   \n",
            "Chabichou                344   192.0     87.2     27.9     90.1     36.3   \n",
            "Chaource                 292   276.0    132.9     25.4    116.4     32.5   \n",
            "Cheddar                  406   172.0    182.3     32.5     76.4      4.9   \n",
            "Comte                    399    92.0    220.5     32.4     55.9      1.3   \n",
            "Coulomniers              308   222.0     79.2     25.6     63.6     21.1   \n",
            "Edam                     327   148.0    272.2     24.7     65.7      5.5   \n",
            "Emmental                 378    60.0    308.2     29.4     56.3      2.4   \n",
            "Fr.chevrepatemolle       206   160.0     72.8     18.5    150.5     31.0   \n",
            "Fr.fondu.45              292   390.0    168.5     24.0     77.4      5.5   \n",
            "Fr.frais20nat.            80    41.0    146.3      3.5     50.0     20.0   \n",
            "Fr.frais40nat.           115    25.0     94.8      7.8     64.3     22.6   \n",
            "Maroilles                338   311.0    236.7     29.1     46.7      3.6   \n",
            "Morbier                  347   285.0    219.0     29.5     57.6      5.8   \n",
            "Parmesan                 381   240.0    334.6     27.5     90.0      5.2   \n",
            "Petitsuisse40            142    22.0     78.2     10.4     63.4     20.4   \n",
            "PontlEveque              300   223.0    156.7     23.4     53.0      4.0   \n",
            "Pyrenees                 355   232.0    178.9     28.0     51.5      6.8   \n",
            "Reblochon                309   272.0    202.3     24.6     73.1      8.1   \n",
            "Rocquefort               370   432.0    162.0     31.2     83.5     13.3   \n",
            "SaintPaulin              298   205.0    261.0     23.3     60.4      6.7   \n",
            "Tome                     321   252.0    125.5     27.3     62.3      6.2   \n",
            "Vacherin                 321   140.0    218.0     29.3     49.2      3.7   \n",
            "Yaourtlaitent.nat.        70    91.0    215.7      3.4     42.9      2.9   \n",
            "\n",
            "                    proteines  cholesterol  magnesium  \n",
            "Fromages                                               \n",
            "CarredelEst              21.0           70         20  \n",
            "Babybel                  22.6           70         27  \n",
            "Beaufort                 26.6          120         41  \n",
            "Bleu                     20.2           90         27  \n",
            "Camembert                23.4           60         20  \n",
            "Cantal                   23.0           90         30  \n",
            "Chabichou                19.5           80         36  \n",
            "Chaource                 17.8           70         25  \n",
            "Cheddar                  26.0          110         28  \n",
            "Comte                    29.2          120         51  \n",
            "Coulomniers              20.5           80         13  \n",
            "Edam                     24.7           80         44  \n",
            "Emmental                 29.4          110         45  \n",
            "Fr.chevrepatemolle       11.1           50         16  \n",
            "Fr.fondu.45              16.8           70         20  \n",
            "Fr.frais20nat.            8.3           10         11  \n",
            "Fr.frais40nat.            7.0           30         10  \n",
            "Maroilles                20.4           90         40  \n",
            "Morbier                  23.6           80         30  \n",
            "Parmesan                 35.7           80         46  \n",
            "Petitsuisse40             9.4           20         10  \n",
            "PontlEveque              21.1           70         22  \n",
            "Pyrenees                 22.4           90         25  \n",
            "Reblochon                19.7           80         30  \n",
            "Rocquefort               18.7          100         25  \n",
            "SaintPaulin              23.3           70         26  \n",
            "Tome                     21.8           80         20  \n",
            "Vacherin                 17.6           80         30  \n",
            "Yaourtlaitent.nat.        4.1           13         14  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Croisement 2 à 2 des variables\n",
        "import pandas as pd\n",
        "# diagonal{‘hist’, ‘kde’}:\n",
        "# Pick between ‘kde’ and ‘hist’ for either Kernel Density Estimation or Histogram plot in the diagonal.\n",
        "pd.plotting.scatter_matrix(fromage, figsize=(9,9), diagonal=\"kde\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "oNIqASXAAXP1",
        "outputId": "2119cc6d-2676-4b55-814d-518404abe8b6"
      },
      "execution_count": null,
      "outputs": [
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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Partie 2 : Méthode des centres mobiles"
      ],
      "metadata": {
        "id": "Iyk7N8Q3dC4l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from sklearn import cluster\n",
        "np.random.seed(0)\n",
        "# Créer um modèle pour un ensemble de k centres.\n",
        "kmeans = cluster.KMeans(n_clusters = 4)\n",
        "# Définir le modèle de clustering.\n",
        "kmeans.fit(fromage)\n",
        "# np.argsort: Returns the indices that would sort an array.\n",
        "idk = np.argsort(kmeans.labels_)\n",
        "print(pd.DataFrame(fromage.index[idk],kmeans.labels_[idk]))\n",
        "# transform(X): transform X to a cluster-distance space.\n",
        "print(kmeans.transform(fromage))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MrSUgIHlB1Lw",
        "outputId": "dba1691d-070b-46ff-c8bd-aee0b9a6ae7b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "             Fromages\n",
            "0         CarredelEst\n",
            "0                Tome\n",
            "0         PontlEveque\n",
            "0           Chabichou\n",
            "0            Chaource\n",
            "0         Coulomniers\n",
            "0  Fr.chevrepatemolle\n",
            "1            Beaufort\n",
            "1         SaintPaulin\n",
            "1             Cheddar\n",
            "1               Comte\n",
            "1                Edam\n",
            "1            Emmental\n",
            "1            Vacherin\n",
            "1            Parmesan\n",
            "2       Petitsuisse40\n",
            "2  Yaourtlaitent.nat.\n",
            "2      Fr.frais20nat.\n",
            "2      Fr.frais40nat.\n",
            "3           Maroilles\n",
            "3             Morbier\n",
            "3              Cantal\n",
            "3           Camembert\n",
            "3            Pyrenees\n",
            "3           Reblochon\n",
            "3          Rocquefort\n",
            "3                Bleu\n",
            "3             Babybel\n",
            "3         Fr.fondu.45\n",
            "[[123.59715669 285.36163076 384.27301005 145.46927992]\n",
            " [110.54651897 118.43379084 303.10311983  71.72681089]\n",
            " [235.25665316  56.72603293 349.91323389 218.1879268 ]\n",
            " [159.09984736 200.30401971 393.76898843  45.60922494]\n",
            " [141.19170858 210.31138298 332.43471728  84.66051854]\n",
            " [180.75982487 111.73150994 371.97076666  86.99931839]\n",
            " [ 72.0404549  182.80599775 298.65300308 170.2611917 ]\n",
            " [ 57.86280572 204.98823213 311.48990553 105.53037193]\n",
            " [156.41570984  92.26223665 348.48685233 159.88151676]\n",
            " [224.31195752  79.32509258 333.83554522 230.88643399]\n",
            " [ 39.94716153 204.4018782  285.29211565 155.61953412]\n",
            " [197.13338124  43.74211715 293.81905359 172.55995306]\n",
            " [289.57992728 102.59674855 343.1669947  273.3780741 ]\n",
            " [144.41931015 265.24828993 195.86579908 252.80069897]\n",
            " [164.74401355 271.72958122 400.47054979 101.45152241]\n",
            " [307.24796873 336.96303256  27.57918146 378.20198492]\n",
            " [286.92623741 330.65941362  48.43507252 376.38946771]\n",
            " [163.69886115 169.20512053 379.74839203  39.80348477]\n",
            " [137.46307556 146.31641334 360.87135     31.87791398]\n",
            " [247.92574637 127.37007228 405.05415842 157.0268493 ]\n",
            " [275.48594208 322.76561591  73.02996816 370.72406639]\n",
            " [ 66.39975258 145.61200264 273.9400961  103.74546448]\n",
            " [103.21034693 118.1602421  327.69454718  85.09362726]\n",
            " [106.4868939  149.56115075 323.02206001  41.96502591]\n",
            " [215.62761551 302.57210349 480.78906108 141.69363218]\n",
            " [163.61948015  93.47945128 289.74900561 120.31124386]\n",
            " [ 44.67517687 176.06769384 309.5039923   98.83002277]\n",
            " [158.9611408   63.47704556 263.14012664 168.16769428]\n",
            " [304.65582689 316.6232269  101.24362326 346.9503587 ]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Détection du nombre adéquat de groupes\n"
      ],
      "metadata": {
        "id": "UYf2hxqwdRVf"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### La métrique silhouette"
      ],
      "metadata": {
        "id": "EUtgwYp7dhIx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# The silhouette coefficient is a measure of cluster cohesion and separation. It quantifies how well a data point fits into its assigned cluster based on two factors:\n",
        "# How close the data point is to other points in the cluster\n",
        "# How far away the data point is from points in other clusters\n",
        "# Silhouette coefficient values range between -1 and 1. Larger numbers indicate that samples are closer to their clusters than they are to other clusters.\n",
        "from sklearn import metrics\n",
        "# Utilisation de la métrique \"silhouette\"\n",
        "res = np.arange(9, dtype =\"double\")\n",
        "for k in np.arange(9):\n",
        "  km = cluster.KMeans(n_clusters = k+2)\n",
        "  km.fit(fromage)\n",
        "  res[k] = metrics.silhouette_score(fromage,km.labels_)\n",
        "print (res)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rpJaxmiFChdc",
        "outputId": "f5569b82-59ba-4ef4-981c-199b478c3533"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0.50681355 0.37299771 0.3282387  0.35737616 0.32267618 0.28114392\n",
            " 0.29450378 0.23904343 0.25006247]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.title(\"silhouette\")\n",
        "plt.xlabel(\"# of clusters\")\n",
        "plt.plot(np.arange(2,11,1),(res))\n",
        "plt.show"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        },
        "id": "XpN5uLqTCjxd",
        "outputId": "7e4862c9-496f-4ad0-ec82-f20f0986880e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show(*args, **kw)>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Partie 3 : Classification ascendante hiérarchique"
      ],
      "metadata": {
        "id": "uj2T-vcKdoFD"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "La classification ascendante hiérarchique (ou CAH) procède par fusions successives\n",
        "d'ensembles de points (clusters), en considérant initialement tous les points comme des\n",
        "clusters singletons, on fusionne à chaque étape les 2 clusters les plus proches au sens d'une\n",
        "distance, jusqu'à obtenir un seul cluster contenant tous les points."
      ],
      "metadata": {
        "id": "Laq5nv5Sd1BN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas\n",
        "import numpy as np\n",
        "#librairies pour la CAH\n",
        "from matplotlib import pyplot as plt\n",
        "from scipy.cluster.hierarchy import dendrogram, linkage, fcluster\n",
        "# linkage: perform hierarchical clustering. \n",
        "# method: for calculating the distance between the newly formed cluster u and each v (any other cluster that is not u)\n",
        "Z = linkage(fromage, method='ward', metric='euclidean')\n",
        "#affichage du dendrogramme\n",
        "plt.title(\"CAH\")\n",
        "plt.title('CAH avec matérialisation des 4 classes')\n",
        "# Plot the hierarchical clustering as a dendrogram\n",
        "dendrogram(Z,labels=fromage.index,orientation='left',color_threshold=255)\n",
        "plt.show()\n",
        "# flcuster: Form flat clusters from the hierarchical clustering defined by the given linkage matrix.\n",
        "# t: this is the threshold to apply when forming flat clusters.\n",
        "groupes_cah = fcluster(Z, t = 255,criterion='distance')\n",
        "print(groupes_cah)\n",
        "#index triés des groupes\n",
        "idg = np.argsort(groupes_cah)\n",
        "#affichage des observations et leurs groupes\n",
        "print(pandas.DataFrame(fromage.index[idg],groupes_cah[idg]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 819
        },
        "id": "HqFimooqCrWw",
        "outputId": "3cefd7a4-c099-4346-ac23-e52bd1d2aab3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[3 4 2 3 3 2 4 4 2 2 4 2 2 4 3 1 1 3 3 2 1 4 4 4 3 2 4 2 1]\n",
            "             Fromages\n",
            "1  Yaourtlaitent.nat.\n",
            "1       Petitsuisse40\n",
            "1      Fr.frais40nat.\n",
            "1      Fr.frais20nat.\n",
            "2         SaintPaulin\n",
            "2            Beaufort\n",
            "2              Cantal\n",
            "2            Parmesan\n",
            "2             Cheddar\n",
            "2               Comte\n",
            "2                Edam\n",
            "2            Emmental\n",
            "2            Vacherin\n",
            "3          Rocquefort\n",
            "3             Morbier\n",
            "3           Maroilles\n",
            "3         CarredelEst\n",
            "3           Camembert\n",
            "3                Bleu\n",
            "3         Fr.fondu.45\n",
            "4         Coulomniers\n",
            "4            Chaource\n",
            "4           Chabichou\n",
            "4         PontlEveque\n",
            "4            Pyrenees\n",
            "4           Reblochon\n",
            "4             Babybel\n",
            "4                Tome\n",
            "4  Fr.chevrepatemolle\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# la correspondance entre les groupes de la CAH et les clusters de Kmeans\n",
        "pd.crosstab(groupes_cah, kmeans.labels_)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "hlvdBiXQLwBr",
        "outputId": "a2009c7f-a8cd-48a6-f969-07728fcce4c7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "col_0  0  1  2  3\n",
              "row_0            \n",
              "1      0  0  4  0\n",
              "2      0  8  0  1\n",
              "3      1  0  0  6\n",
              "4      6  0  0  3"
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              "        const buttonEl =\n",
              "          document.querySelector('#df-946e8e70-bfa4-45b0-b09c-0b800f0acce7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-946e8e70-bfa4-45b0-b09c-0b800f0acce7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Partie 4 : Interprétation des classes"
      ],
      "metadata": {
        "id": "ZESrI-nZgXb9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Analyse en composantes principales (ACP)"
      ],
      "metadata": {
        "id": "YkRoMXnkge66"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        " Reducing the dimensionality of the Data "
      ],
      "metadata": {
        "id": "HcBxChk8jUd4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.decomposition import PCA\n",
        "# n_components: Number of components to keep. if n_components is not set all components are kept\n",
        "# n_components == min(n_samples, n_features)\n",
        "# fit_transform: Fit the model with X and apply the dimensionality reduction on X.\n",
        "acp = PCA(n_components = 2).fit_transform(fromage)\n",
        "for couleur,k in zip(['red','blue','lawngreen', 'aqua'],[0,1,2,3]):\n",
        "  plt.scatter(acp[kmeans.labels_==k,0],acp[kmeans.labels_==k,1],c=couleur)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "JmyXxx9UDYrD",
        "outputId": "241196e9-5bff-4e1a-f67f-c1240d24084c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# CR: La méthode AgglomerativeClustering:"
      ],
      "metadata": {
        "id": "EwpEPpuiiduz"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Recursively merges pair of clusters of sample data; uses linkage distance."
      ],
      "metadata": {
        "id": "fg5vg_BPi1Gw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.cluster import AgglomerativeClustering\n",
        "\n",
        "ac = AgglomerativeClustering(n_clusters = 4)\n",
        "ac.fit(fromage)\n",
        "labels = ac.labels_\n",
        "print(labels)\n",
        "# np.argsort: Returns the indices that would sort an array.\n",
        "idk = np.argsort(ac.labels_)\n",
        "print(pd.DataFrame(fromage.index[idk],ac.labels_[idk]))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QlRxe0UsisXB",
        "outputId": "c7fd0f41-29ee-4518-a1d8-0d0743ce133b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[1 2 0 1 1 0 2 2 0 0 2 0 0 2 1 3 3 1 1 0 3 2 2 2 1 0 2 0 3]\n",
            "             Fromages\n",
            "0         SaintPaulin\n",
            "0            Beaufort\n",
            "0            Parmesan\n",
            "0              Cantal\n",
            "0             Cheddar\n",
            "0               Comte\n",
            "0            Vacherin\n",
            "0                Edam\n",
            "0            Emmental\n",
            "1         CarredelEst\n",
            "1          Rocquefort\n",
            "1             Morbier\n",
            "1           Maroilles\n",
            "1         Fr.fondu.45\n",
            "1           Camembert\n",
            "1                Bleu\n",
            "2         Coulomniers\n",
            "2            Chaource\n",
            "2           Chabichou\n",
            "2         PontlEveque\n",
            "2            Pyrenees\n",
            "2           Reblochon\n",
            "2             Babybel\n",
            "2                Tome\n",
            "2  Fr.chevrepatemolle\n",
            "3      Fr.frais20nat.\n",
            "3      Fr.frais40nat.\n",
            "3       Petitsuisse40\n",
            "3  Yaourtlaitent.nat.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for couleur,k in zip(['red','blue','lawngreen', 'aqua'],[0,1,2,3]):\n",
        "  plt.scatter(acp[ac.labels_==k,0],acp[ac.labels_==k,1],c=couleur)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "Nz0O4oDFm2xA",
        "outputId": "35bca871-5c95-454e-b871-096ebd3b4cb7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for couleur,k in zip(['red','blue','lawngreen', 'aqua'],[1,2,3,4]):\n",
        "  plt.scatter(acp[groupes_cah==k,0],acp[groupes_cah==k,1],c=couleur)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "id": "xG6S4oc0pBaG",
        "outputId": "ad945d79-cf35-4f63-89fa-8c6282890147"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "qeNK66di_r1U"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def DIANA_based_on_KMeans():\n",
        "    def split(group):\n",
        "        np.random.seed(0)\n",
        "        kmeans = cluster.KMeans(n_clusters=2).fit(group)\n",
        "        cluster0 = group[kmeans.labels_ == 0]\n",
        "        cluster1 = group[kmeans.labels_ == 1]\n",
        "        # print(kmeans.cluster_centers_[0])\n",
        "        distance = metrics.pairwise.euclidean_distances(\n",
        "            [kmeans.cluster_centers_[0]], [kmeans.cluster_centers_[1]])\n",
        "        return [cluster0, cluster1, distance[0][0]]\n",
        "\n",
        "    def adjust_linkage_pointers(linkage, n_samples):\n",
        "        adjusted_linkage = []\n",
        "        for i, [index0, index1, distance, size] in enumerate(linkage):\n",
        "            if(index0 < 0):\n",
        "                index0 = n_samples+i+index0\n",
        "            if(index1 < 0):\n",
        "                index1 = n_samples+i+index1\n",
        "            adjusted_linkage += [[float(index0), float(index1),\n",
        "                                  float(distance), float(size)]]\n",
        "\n",
        "        return adjusted_linkage\n",
        "\n",
        "    fromage = pd.read_table(r\"/content/fromage1.txt\", sep=\"\\t\", header=0, index_col=0)\n",
        "    groups = [fromage]\n",
        "\n",
        "    linkage = []\n",
        "    maxDistance = 60\n",
        "    i = 0\n",
        "    while(i < len(groups)):\n",
        "        currentGroup = groups[i]\n",
        "        [cluster0, cluster1,distance] = split(currentGroup)\n",
        "\n",
        "        if(len(cluster0) == 1):\n",
        "            index0 = fromage.index.get_loc(cluster0.index[0])\n",
        "            if(len(cluster1) == 1):\n",
        "                index1 = fromage.index.get_loc(cluster1.index[0])\n",
        "            else:\n",
        "                index1 = i-len(groups)\n",
        "                groups += [cluster1]\n",
        "        else:\n",
        "            index0 = i-len(groups)\n",
        "            if(len(cluster1) == 1):\n",
        "                index1 = fromage.index.get_loc(cluster1.index[0])\n",
        "            else:\n",
        "                index1 = i-len(groups)-1\n",
        "                groups += [cluster1]\n",
        "            groups += [cluster0]\n",
        "\n",
        "        # distance = maxDistance-2*i\n",
        "        size = len(currentGroup)\n",
        "        linkage.insert(0, [index0, index1, distance, size])\n",
        "\n",
        "        i += 1\n",
        "\n",
        "    linkage = adjust_linkage_pointers(linkage, len(fromage))\n",
        "    dendrogram(linkage, labels=fromage.index,\n",
        "               orientation='left', color_threshold=150)\n",
        "\n",
        "    plt.show()\n",
        "\n",
        "\n",
        "DIANA_based_on_KMeans()"
      ],
      "metadata": {
        "id": "XDgkP_H-4ZgU",
        "outputId": "443b4fce-9fcd-41f7-cfe3-a51f3b5355ee",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 266
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
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          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}