Prediction using Unsupervised ML/Unsupervised ML.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "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": "3.7.4"
    },
    "colab": {
      "name": "TSF Task#3.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Kushal997-das/THE-SPARKS-FOUNDATION/blob/master/Task-3/TSF%20Task%233.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7C1URD2qu3xU"
      },
      "source": [
        "## Task-3: To Explore Unsupervised Machine Learning"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y3MLSNjgu3xd"
      },
      "source": [
        "<h2>Importing libraries:</h2>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rs4xqiTZu3xf"
      },
      "source": [
        "from sklearn.cluster import KMeans\n",
        "import pandas as pd\n",
        "import seaborn as sns\n",
        "from matplotlib import pyplot as plt\n",
        "%matplotlib inline"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fsXLwgvuu3xl"
      },
      "source": [
        "### Load the iris dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pMa2Z6XKu3xm"
      },
      "source": [
        "df=pd.read_csv('Iris.csv')\n",
        "df.drop(['Id'],axis=1,inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OepUVYP-u3xq"
      },
      "source": [
        "### Reading the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nrGfLwLku3xq",
        "outputId": "e082535f-5cd7-47ca-9f15-d94152c69a7a"
      },
      "source": [
        "df.head() #diplay the fisrt 5 dataset."
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SepalLengthCm</th>\n",
              "      <th>SepalWidthCm</th>\n",
              "      <th>PetalLengthCm</th>\n",
              "      <th>PetalWidthCm</th>\n",
              "      <th>Species</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>Iris-setosa</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm      Species\n",
              "0            5.1           3.5            1.4           0.2  Iris-setosa\n",
              "1            4.9           3.0            1.4           0.2  Iris-setosa\n",
              "2            4.7           3.2            1.3           0.2  Iris-setosa\n",
              "3            4.6           3.1            1.5           0.2  Iris-setosa\n",
              "4            5.0           3.6            1.4           0.2  Iris-setosa"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tiPSHpEGu3xu",
        "outputId": "24e6ed71-6727-4073-dccc-33bfd4380ce5"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(150, 5)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1M8__nIFu3xx",
        "outputId": "d16a3e05-69b5-41a3-963f-d934fba77d92"
      },
      "source": [
        "df.info()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 150 entries, 0 to 149\n",
            "Data columns (total 5 columns):\n",
            "SepalLengthCm    150 non-null float64\n",
            "SepalWidthCm     150 non-null float64\n",
            "PetalLengthCm    150 non-null float64\n",
            "PetalWidthCm     150 non-null float64\n",
            "Species          150 non-null object\n",
            "dtypes: float64(4), object(1)\n",
            "memory usage: 6.0+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "upRB_8tku3xz",
        "outputId": "3983347d-930c-44dd-d5d1-c70da07f02f6"
      },
      "source": [
        "df.describe()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SepalLengthCm</th>\n",
              "      <th>SepalWidthCm</th>\n",
              "      <th>PetalLengthCm</th>\n",
              "      <th>PetalWidthCm</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>count</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>150.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>mean</td>\n",
              "      <td>5.843333</td>\n",
              "      <td>3.054000</td>\n",
              "      <td>3.758667</td>\n",
              "      <td>1.198667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>std</td>\n",
              "      <td>0.828066</td>\n",
              "      <td>0.433594</td>\n",
              "      <td>1.764420</td>\n",
              "      <td>0.763161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>min</td>\n",
              "      <td>4.300000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25%</td>\n",
              "      <td>5.100000</td>\n",
              "      <td>2.800000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>0.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50%</td>\n",
              "      <td>5.800000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>4.350000</td>\n",
              "      <td>1.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75%</td>\n",
              "      <td>6.400000</td>\n",
              "      <td>3.300000</td>\n",
              "      <td>5.100000</td>\n",
              "      <td>1.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>max</td>\n",
              "      <td>7.900000</td>\n",
              "      <td>4.400000</td>\n",
              "      <td>6.900000</td>\n",
              "      <td>2.500000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm\n",
              "count     150.000000    150.000000     150.000000    150.000000\n",
              "mean        5.843333      3.054000       3.758667      1.198667\n",
              "std         0.828066      0.433594       1.764420      0.763161\n",
              "min         4.300000      2.000000       1.000000      0.100000\n",
              "25%         5.100000      2.800000       1.600000      0.300000\n",
              "50%         5.800000      3.000000       4.350000      1.300000\n",
              "75%         6.400000      3.300000       5.100000      1.800000\n",
              "max         7.900000      4.400000       6.900000      2.500000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SBIyQEv0u3x2",
        "outputId": "b5edf46a-fcea-4839-da98-855ff6f3997f"
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SepalLengthCm    0\n",
              "SepalWidthCm     0\n",
              "PetalLengthCm    0\n",
              "PetalWidthCm     0\n",
              "Species          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gF6QR4Cau3x5"
      },
      "source": [
        "df.drop_duplicates(inplace=True)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UZCCacReu3x7"
      },
      "source": [
        "### Label Encoding"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oHGBylgUu3x8",
        "outputId": "e8820a79-0f89-4d71-af67-3e71a1e24713"
      },
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "le=LabelEncoder()\n",
        "df['Species']=le.fit_transform(df['Species'])\n",
        "df['Species'].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    50\n",
              "2    49\n",
              "0    48\n",
              "Name: Species, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b8e6GxoKu3x-"
      },
      "source": [
        "### PetalLengthCm vs PetalWidthCm \n",
        ">*we'll compare our final plot with this graph to check how accurate our model is*"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NRmFl5G_u3x-",
        "outputId": "37559ca4-1929-4e83-ee51-e8cb03563d02"
      },
      "source": [
        "plt.scatter(df['PetalLengthCm'],df['PetalWidthCm'],c=df.Species.values)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.collections.PathCollection at 0x1487bc7e408>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "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"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_XcYyRGQu3yB",
        "outputId": "6d26aef8-2265-45b1-aa50-b30cc27c0edb"
      },
      "source": [
        "df.corr()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SepalLengthCm</th>\n",
              "      <th>SepalWidthCm</th>\n",
              "      <th>PetalLengthCm</th>\n",
              "      <th>PetalWidthCm</th>\n",
              "      <th>Species</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>SepalLengthCm</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.109321</td>\n",
              "      <td>0.871305</td>\n",
              "      <td>0.817058</td>\n",
              "      <td>0.782904</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>SepalWidthCm</td>\n",
              "      <td>-0.109321</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.421057</td>\n",
              "      <td>-0.356376</td>\n",
              "      <td>-0.418348</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>PetalLengthCm</td>\n",
              "      <td>0.871305</td>\n",
              "      <td>-0.421057</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.961883</td>\n",
              "      <td>0.948339</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>PetalWidthCm</td>\n",
              "      <td>0.817058</td>\n",
              "      <td>-0.356376</td>\n",
              "      <td>0.961883</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.955693</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>Species</td>\n",
              "      <td>0.782904</td>\n",
              "      <td>-0.418348</td>\n",
              "      <td>0.948339</td>\n",
              "      <td>0.955693</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               SepalLengthCm  SepalWidthCm  PetalLengthCm  PetalWidthCm  \\\n",
              "SepalLengthCm       1.000000     -0.109321       0.871305      0.817058   \n",
              "SepalWidthCm       -0.109321      1.000000      -0.421057     -0.356376   \n",
              "PetalLengthCm       0.871305     -0.421057       1.000000      0.961883   \n",
              "PetalWidthCm        0.817058     -0.356376       0.961883      1.000000   \n",
              "Species             0.782904     -0.418348       0.948339      0.955693   \n",
              "\n",
              "                Species  \n",
              "SepalLengthCm  0.782904  \n",
              "SepalWidthCm  -0.418348  \n",
              "PetalLengthCm  0.948339  \n",
              "PetalWidthCm   0.955693  \n",
              "Species        1.000000  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eUct3Kmiu3yD"
      },
      "source": [
        "### Data Visualization"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IPaotKG4u3yD",
        "outputId": "b58e88f0-b4ff-4b51-8bda-2684c33315b0"
      },
      "source": [
        "fig=plt.figure(figsize=(15,12))\n",
        "sns.heatmap(df.corr(),linewidths=1,annot=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x1487bce9f88>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x864 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7FUMarWDu3yF",
        "outputId": "2475ee56-aa0b-4288-de0c-e8b2f666db68"
      },
      "source": [
        "sns.pairplot(df)\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<seaborn.axisgrid.PairGrid at 0x1487cda6548>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 900x900 with 30 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "df83ww2Pu3yH"
      },
      "source": [
        ">We can see that Species is mainly depend on Petal Length and Petal Width."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3ZJ7DfWAu3yH"
      },
      "source": [
        ">using petal_length and petal_width\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DBd0oYAFu3yI"
      },
      "source": [
        "df=df.iloc[:,[0,1,2,3]].values"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "poq-X9_fu3yK"
      },
      "source": [
        "### Elbow Method using within-cluster-sum-of-squares(wcss) "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EFYsQ3Bxu3yL",
        "outputId": "e3a0bb4a-72be-40e1-81a9-42159a2ca958"
      },
      "source": [
        "from sklearn.cluster import KMeans\n",
        "wcss = []\n",
        "for i in range(1, 11):\n",
        "    kmeans = KMeans(n_clusters = i, init = 'k-means++', random_state = 42)\n",
        "    kmeans.fit(df)\n",
        "    # inertia method returns wcss for that model\n",
        "    wcss.append(kmeans.inertia_)\n",
        "    \n",
        "wcss"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[663.895238095238,\n",
              " 151.77145833333336,\n",
              " 77.91989035087718,\n",
              " 56.64237065018315,\n",
              " 45.816421929824564,\n",
              " 38.380978808131445,\n",
              " 34.11707094757095,\n",
              " 29.75801580972634,\n",
              " 27.74499792038028,\n",
              " 25.769652682285034]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E9DVlDw1u3yO"
      },
      "source": [
        "### Using Elbow graph to find optimum no. of Clusters"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FpUxiK-Ku3yP",
        "outputId": "73fa01e2-e861-4838-bbe3-a77514d6900f"
      },
      "source": [
        "plt.figure(figsize=(10,5))\n",
        "sns.set(style='whitegrid')\n",
        "sns.lineplot(range(1, 11), wcss,marker='o',color='red')\n",
        "plt.title('The Elbow Method')\n",
        "plt.xlabel('Number of clusters')\n",
        "plt.ylabel('WCSS')\n",
        "plt.show()\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zqG4hVs3u3yR"
      },
      "source": [
        ">The optimum value for K would be 3. As we can see that with an increase in the number of clusters the WCSS value decreases. We select the value for K on the basis of the rate of decrease in WCSS and we can see that after 3 the drop in wcss is minimal."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OmHkqhAZu3yR"
      },
      "source": [
        "### Initialization using K-means++"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kuEZLSreu3yR",
        "outputId": "179af9b2-0a7c-4996-c5e7-98176e7aca1f"
      },
      "source": [
        "kmeans = KMeans(n_clusters = 3, init = 'k-means++', random_state = 5)\n",
        "y_kmeans = kmeans.fit_predict(df)\n",
        "y_kmeans"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
              "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
              "       1, 1, 1, 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n",
              "       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2,\n",
              "       2, 0, 0, 2, 2, 2, 2, 0, 2, 0, 2, 0, 2, 2, 0, 0, 2, 2, 2, 2, 2, 0,\n",
              "       2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 0, 2, 2, 0])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z1Nv0pwzu3yT"
      },
      "source": [
        "### Visualizing the Clusters "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0thBMJh1u3yU",
        "outputId": "57e33060-649b-4701-8036-93d1cdf07fdb"
      },
      "source": [
        "fig = plt.figure(figsize=(10, 7))\n",
        "plt.title('Clusters with Centroids',fontweight ='bold', fontsize=20)\n",
        "plt.scatter(df[y_kmeans == 0, 2], df[y_kmeans == 0, 3], s = 100, c = 'seagreen', label = 'Iris-versicolour')\n",
        "plt.scatter(df[y_kmeans == 1, 2], df[y_kmeans == 1, 3], s = 100, c = 'purple', label = 'Iris-setosa')\n",
        "plt.scatter(df[y_kmeans == 2, 2], df[y_kmeans == 2, 3],s = 100, c = 'yellow', label = 'Iris-virginica')\n",
        "plt.scatter(kmeans.cluster_centers_[:, 2], kmeans.cluster_centers_[:,3], s = 300, c = 'red',marker='*', \n",
        "            label = 'Centroids')\n",
        "plt.title('Iris Flower Clusters')\n",
        "plt.ylabel('Petal Width in cm')\n",
        "plt.xlabel('Petal Length in cm')\n",
        "plt.legend()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x1487ef295c8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 720x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BxGF0Y2Tu3yV"
      },
      "source": [
        ">We can see that our predicted graph is quite similar to the actual one."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ngqdkuJUu3yW"
      },
      "source": [
        "<h2>Task-3</h2> <br>\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fq-YrIC6u3yW"
      },
      "source": [
        "__Completed__"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5glKoovTu3yW"
      },
      "source": [
        ">Thank You! <br>\n",
        ">>Kushal Das"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fbXrfugsu3yX"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}