PRML_Project.ipynb

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    "colab": {
      "name": "PRML-Project.ipynb",
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      "collapsed_sections": [],
      "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/vaishnavipatil29/Career-Guidance-ML-Project/blob/master/PRML_Project.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vSlFV9d1CP8v",
        "outputId": "6c75a869-9496-45be-98aa-7d9c99f0ab4f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 445
        }
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "#df=pd.read_csv(\"career_pred.csv\")\n",
        "url='https://raw.githubusercontent.com/vaishnavipatil29/Career-Guidance-ML-Project/master/career_pred.csv'\n",
        "df = pd.read_csv(url)\n",
        "df.head()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Acedamic percentage in Operating Systems</th>\n",
              "      <th>percentage in Algorithms</th>\n",
              "      <th>Percentage in Programming Concepts</th>\n",
              "      <th>Percentage in Software Engineering</th>\n",
              "      <th>Percentage in Computer Networks</th>\n",
              "      <th>Percentage in Electronics Subjects</th>\n",
              "      <th>Percentage in Computer Architecture</th>\n",
              "      <th>Percentage in Mathematics</th>\n",
              "      <th>Percentage in Communication skills</th>\n",
              "      <th>Hours working per day</th>\n",
              "      <th>Logical quotient rating</th>\n",
              "      <th>hackathons</th>\n",
              "      <th>coding skills rating</th>\n",
              "      <th>public speaking points</th>\n",
              "      <th>can work long time before system?</th>\n",
              "      <th>self-learning capability?</th>\n",
              "      <th>Extra-courses did</th>\n",
              "      <th>certifications</th>\n",
              "      <th>workshops</th>\n",
              "      <th>talenttests taken?</th>\n",
              "      <th>olympiads</th>\n",
              "      <th>reading and writing skills</th>\n",
              "      <th>memory capability score</th>\n",
              "      <th>Interested subjects</th>\n",
              "      <th>interested career area</th>\n",
              "      <th>Job/Higher Studies?</th>\n",
              "      <th>Type of company want to settle in?</th>\n",
              "      <th>Taken inputs from seniors or elders</th>\n",
              "      <th>interested in games</th>\n",
              "      <th>Interested Type of Books</th>\n",
              "      <th>Salary Range Expected</th>\n",
              "      <th>In a Realtionship?</th>\n",
              "      <th>Gentle or Tuff behaviour?</th>\n",
              "      <th>Management or Technical</th>\n",
              "      <th>Salary/work</th>\n",
              "      <th>hard/smart worker</th>\n",
              "      <th>worked in teams ever?</th>\n",
              "      <th>Introvert</th>\n",
              "      <th>Suggested Job Role</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>69</td>\n",
              "      <td>63</td>\n",
              "      <td>78</td>\n",
              "      <td>87</td>\n",
              "      <td>94</td>\n",
              "      <td>94</td>\n",
              "      <td>87</td>\n",
              "      <td>84</td>\n",
              "      <td>61</td>\n",
              "      <td>9</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>8</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>shell programming</td>\n",
              "      <td>cloud computing</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>excellent</td>\n",
              "      <td>excellent</td>\n",
              "      <td>cloud computing</td>\n",
              "      <td>system developer</td>\n",
              "      <td>higherstudies</td>\n",
              "      <td>Web Services</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>Prayer books</td>\n",
              "      <td>salary</td>\n",
              "      <td>no</td>\n",
              "      <td>stubborn</td>\n",
              "      <td>Management</td>\n",
              "      <td>salary</td>\n",
              "      <td>hard worker</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>Database Developer</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>78</td>\n",
              "      <td>62</td>\n",
              "      <td>73</td>\n",
              "      <td>60</td>\n",
              "      <td>71</td>\n",
              "      <td>70</td>\n",
              "      <td>73</td>\n",
              "      <td>84</td>\n",
              "      <td>91</td>\n",
              "      <td>12</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>machine learning</td>\n",
              "      <td>database security</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>poor</td>\n",
              "      <td>medium</td>\n",
              "      <td>networks</td>\n",
              "      <td>Business process analyst</td>\n",
              "      <td>job</td>\n",
              "      <td>SAaS services</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>Childrens</td>\n",
              "      <td>salary</td>\n",
              "      <td>yes</td>\n",
              "      <td>gentle</td>\n",
              "      <td>Technical</td>\n",
              "      <td>salary</td>\n",
              "      <td>hard worker</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>Portal Administrator</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>71</td>\n",
              "      <td>86</td>\n",
              "      <td>91</td>\n",
              "      <td>87</td>\n",
              "      <td>61</td>\n",
              "      <td>81</td>\n",
              "      <td>72</td>\n",
              "      <td>72</td>\n",
              "      <td>94</td>\n",
              "      <td>11</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>app development</td>\n",
              "      <td>web technologies</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>poor</td>\n",
              "      <td>excellent</td>\n",
              "      <td>hacking</td>\n",
              "      <td>developer</td>\n",
              "      <td>higherstudies</td>\n",
              "      <td>Sales and Marketing</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>Travel</td>\n",
              "      <td>Work</td>\n",
              "      <td>no</td>\n",
              "      <td>stubborn</td>\n",
              "      <td>Management</td>\n",
              "      <td>work</td>\n",
              "      <td>hard worker</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>Portal Administrator</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>76</td>\n",
              "      <td>87</td>\n",
              "      <td>60</td>\n",
              "      <td>84</td>\n",
              "      <td>89</td>\n",
              "      <td>73</td>\n",
              "      <td>62</td>\n",
              "      <td>88</td>\n",
              "      <td>69</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>python</td>\n",
              "      <td>data science</td>\n",
              "      <td>yes</td>\n",
              "      <td>no</td>\n",
              "      <td>medium</td>\n",
              "      <td>excellent</td>\n",
              "      <td>networks</td>\n",
              "      <td>testing</td>\n",
              "      <td>higherstudies</td>\n",
              "      <td>Testing and Maintainance Services</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>Romance</td>\n",
              "      <td>Work</td>\n",
              "      <td>yes</td>\n",
              "      <td>gentle</td>\n",
              "      <td>Management</td>\n",
              "      <td>work</td>\n",
              "      <td>smart worker</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>Systems Security Administrator</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>92</td>\n",
              "      <td>62</td>\n",
              "      <td>90</td>\n",
              "      <td>67</td>\n",
              "      <td>71</td>\n",
              "      <td>89</td>\n",
              "      <td>73</td>\n",
              "      <td>71</td>\n",
              "      <td>73</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>app development</td>\n",
              "      <td>cloud computing</td>\n",
              "      <td>no</td>\n",
              "      <td>no</td>\n",
              "      <td>poor</td>\n",
              "      <td>excellent</td>\n",
              "      <td>Computer Architecture</td>\n",
              "      <td>testing</td>\n",
              "      <td>higherstudies</td>\n",
              "      <td>product development</td>\n",
              "      <td>no</td>\n",
              "      <td>yes</td>\n",
              "      <td>Cookbooks</td>\n",
              "      <td>salary</td>\n",
              "      <td>no</td>\n",
              "      <td>stubborn</td>\n",
              "      <td>Management</td>\n",
              "      <td>work</td>\n",
              "      <td>hard worker</td>\n",
              "      <td>yes</td>\n",
              "      <td>yes</td>\n",
              "      <td>Business Systems Analyst</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Acedamic percentage in Operating Systems  ...              Suggested Job Role\n",
              "0                                        69  ...              Database Developer\n",
              "1                                        78  ...            Portal Administrator\n",
              "2                                        71  ...            Portal Administrator\n",
              "3                                        76  ...  Systems Security Administrator\n",
              "4                                        92  ...        Business Systems Analyst\n",
              "\n",
              "[5 rows x 39 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wx4V4K8sW6Ah"
      },
      "source": [
        "# Data\n",
        "data = df.iloc[:,:-1].values\n",
        "label = df.iloc[:,-1]"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gxhXkR4aXoIW"
      },
      "source": [
        "#Label Encoding: COnverting To Numeric values\n",
        "from sklearn.preprocessing import LabelEncoder, OneHotEncoder\n",
        "labelencoder = LabelEncoder()\n",
        "\n",
        "for i in range(14,38):\n",
        "    data[:,i] = labelencoder.fit_transform(data[:,i])\n",
        "\n",
        "#Normalizing the data\n",
        "from sklearn.preprocessing import Normalizer\n",
        "data1=data[:,:14]\n",
        "normalized_data = Normalizer().fit_transform(data1)\n",
        "\n",
        "data2=data[:,14:]\n",
        "df1 = np.append(normalized_data,data2,axis=1)\n"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VzG5JwH3YiVs",
        "outputId": "242ed10a-7bc8-4cc3-93e5-52c50685df9a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 524
        }
      },
      "source": [
        "#Combining into a dataset\n",
        "df2=df.iloc[:,:-1]\n",
        "dataset = pd.DataFrame(df1,columns=df2.columns)\n",
        "dataset"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Acedamic percentage in Operating Systems</th>\n",
              "      <th>percentage in Algorithms</th>\n",
              "      <th>Percentage in Programming Concepts</th>\n",
              "      <th>Percentage in Software Engineering</th>\n",
              "      <th>Percentage in Computer Networks</th>\n",
              "      <th>Percentage in Electronics Subjects</th>\n",
              "      <th>Percentage in Computer Architecture</th>\n",
              "      <th>Percentage in Mathematics</th>\n",
              "      <th>Percentage in Communication skills</th>\n",
              "      <th>Hours working per day</th>\n",
              "      <th>Logical quotient rating</th>\n",
              "      <th>hackathons</th>\n",
              "      <th>coding skills rating</th>\n",
              "      <th>public speaking points</th>\n",
              "      <th>can work long time before system?</th>\n",
              "      <th>self-learning capability?</th>\n",
              "      <th>Extra-courses did</th>\n",
              "      <th>certifications</th>\n",
              "      <th>workshops</th>\n",
              "      <th>talenttests taken?</th>\n",
              "      <th>olympiads</th>\n",
              "      <th>reading and writing skills</th>\n",
              "      <th>memory capability score</th>\n",
              "      <th>Interested subjects</th>\n",
              "      <th>interested career area</th>\n",
              "      <th>Job/Higher Studies?</th>\n",
              "      <th>Type of company want to settle in?</th>\n",
              "      <th>Taken inputs from seniors or elders</th>\n",
              "      <th>interested in games</th>\n",
              "      <th>Interested Type of Books</th>\n",
              "      <th>Salary Range Expected</th>\n",
              "      <th>In a Realtionship?</th>\n",
              "      <th>Gentle or Tuff behaviour?</th>\n",
              "      <th>Management or Technical</th>\n",
              "      <th>Salary/work</th>\n",
              "      <th>hard/smart worker</th>\n",
              "      <th>worked in teams ever?</th>\n",
              "      <th>Introvert</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.28509</td>\n",
              "      <td>0.260299</td>\n",
              "      <td>0.322276</td>\n",
              "      <td>0.359461</td>\n",
              "      <td>0.388383</td>\n",
              "      <td>0.388383</td>\n",
              "      <td>0.359461</td>\n",
              "      <td>0.347066</td>\n",
              "      <td>0.252036</td>\n",
              "      <td>0.0371856</td>\n",
              "      <td>0.016527</td>\n",
              "      <td>0</td>\n",
              "      <td>0.016527</td>\n",
              "      <td>0.0330539</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>21</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.34998</td>\n",
              "      <td>0.278189</td>\n",
              "      <td>0.327545</td>\n",
              "      <td>0.269215</td>\n",
              "      <td>0.318571</td>\n",
              "      <td>0.314085</td>\n",
              "      <td>0.327545</td>\n",
              "      <td>0.376901</td>\n",
              "      <td>0.40831</td>\n",
              "      <td>0.0538431</td>\n",
              "      <td>0.0314085</td>\n",
              "      <td>0.00448692</td>\n",
              "      <td>0.00897384</td>\n",
              "      <td>0.0134608</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.295012</td>\n",
              "      <td>0.357339</td>\n",
              "      <td>0.378115</td>\n",
              "      <td>0.361494</td>\n",
              "      <td>0.253461</td>\n",
              "      <td>0.336563</td>\n",
              "      <td>0.299168</td>\n",
              "      <td>0.299168</td>\n",
              "      <td>0.39058</td>\n",
              "      <td>0.0457062</td>\n",
              "      <td>0.0041551</td>\n",
              "      <td>0.0166204</td>\n",
              "      <td>0.0041551</td>\n",
              "      <td>0.0124653</td>\n",
              "      <td>1</td>\n",
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              "      <td>1</td>\n",
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              "      <td>2</td>\n",
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              "      <td>6</td>\n",
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              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>29</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.328025</td>\n",
              "      <td>0.375503</td>\n",
              "      <td>0.258967</td>\n",
              "      <td>0.362554</td>\n",
              "      <td>0.384135</td>\n",
              "      <td>0.315077</td>\n",
              "      <td>0.2676</td>\n",
              "      <td>0.379819</td>\n",
              "      <td>0.297812</td>\n",
              "      <td>0.0302129</td>\n",
              "      <td>0.00431612</td>\n",
              "      <td>0.00431612</td>\n",
              "      <td>0.00863224</td>\n",
              "      <td>0.0215806</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.397157</td>\n",
              "      <td>0.267649</td>\n",
              "      <td>0.388523</td>\n",
              "      <td>0.289234</td>\n",
              "      <td>0.306502</td>\n",
              "      <td>0.384206</td>\n",
              "      <td>0.315136</td>\n",
              "      <td>0.306502</td>\n",
              "      <td>0.315136</td>\n",
              "      <td>0.0172677</td>\n",
              "      <td>0.0215846</td>\n",
              "      <td>0.0172677</td>\n",
              "      <td>0.0259016</td>\n",
              "      <td>0.0129508</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19995</th>\n",
              "      <td>0.366575</td>\n",
              "      <td>0.29591</td>\n",
              "      <td>0.273827</td>\n",
              "      <td>0.278244</td>\n",
              "      <td>0.357742</td>\n",
              "      <td>0.326826</td>\n",
              "      <td>0.397491</td>\n",
              "      <td>0.370992</td>\n",
              "      <td>0.304743</td>\n",
              "      <td>0.0176663</td>\n",
              "      <td>0.00883314</td>\n",
              "      <td>0.0264994</td>\n",
              "      <td>0.00441657</td>\n",
              "      <td>0.0353326</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>17</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19996</th>\n",
              "      <td>0.34342</td>\n",
              "      <td>0.2962</td>\n",
              "      <td>0.356299</td>\n",
              "      <td>0.37347</td>\n",
              "      <td>0.352006</td>\n",
              "      <td>0.283322</td>\n",
              "      <td>0.283322</td>\n",
              "      <td>0.394933</td>\n",
              "      <td>0.287615</td>\n",
              "      <td>0.0300493</td>\n",
              "      <td>0.034342</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0386348</td>\n",
              "      <td>0.034342</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19997</th>\n",
              "      <td>0.343084</td>\n",
              "      <td>0.289348</td>\n",
              "      <td>0.330683</td>\n",
              "      <td>0.359618</td>\n",
              "      <td>0.264546</td>\n",
              "      <td>0.351351</td>\n",
              "      <td>0.285214</td>\n",
              "      <td>0.388553</td>\n",
              "      <td>0.363751</td>\n",
              "      <td>0.0289348</td>\n",
              "      <td>0.0124006</td>\n",
              "      <td>0.0248012</td>\n",
              "      <td>0.00826707</td>\n",
              "      <td>0.0124006</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19998</th>\n",
              "      <td>0.294792</td>\n",
              "      <td>0.377161</td>\n",
              "      <td>0.394502</td>\n",
              "      <td>0.381496</td>\n",
              "      <td>0.286122</td>\n",
              "      <td>0.320804</td>\n",
              "      <td>0.264446</td>\n",
              "      <td>0.377161</td>\n",
              "      <td>0.264446</td>\n",
              "      <td>0.0216759</td>\n",
              "      <td>0.00433518</td>\n",
              "      <td>0.0173407</td>\n",
              "      <td>0.0390166</td>\n",
              "      <td>0.0216759</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>29</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19999</th>\n",
              "      <td>0.311409</td>\n",
              "      <td>0.328472</td>\n",
              "      <td>0.315675</td>\n",
              "      <td>0.358334</td>\n",
              "      <td>0.298611</td>\n",
              "      <td>0.277282</td>\n",
              "      <td>0.392461</td>\n",
              "      <td>0.311409</td>\n",
              "      <td>0.383929</td>\n",
              "      <td>0.0298611</td>\n",
              "      <td>0.0127976</td>\n",
              "      <td>0.00426588</td>\n",
              "      <td>0.0298611</td>\n",
              "      <td>0.0255953</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>20000 rows × 38 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Acedamic percentage in Operating Systems  ... Introvert\n",
              "0                                      0.28509  ...         0\n",
              "1                                      0.34998  ...         1\n",
              "2                                     0.295012  ...         1\n",
              "3                                     0.328025  ...         1\n",
              "4                                     0.397157  ...         1\n",
              "...                                        ...  ...       ...\n",
              "19995                                 0.366575  ...         0\n",
              "19996                                  0.34342  ...         1\n",
              "19997                                 0.343084  ...         1\n",
              "19998                                 0.294792  ...         0\n",
              "19999                                 0.311409  ...         0\n",
              "\n",
              "[20000 rows x 38 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RSugN--dZIbu"
      },
      "source": [
        "# For label\n",
        "label = df.iloc[:,-1]\n",
        "original=label.unique() \n",
        "label=label.values\n",
        "label2 = labelencoder.fit_transform(label)\n",
        "y=pd.DataFrame(label2,columns=[\"Suggested Job Role\"])\n",
        "numeric=y[\"Suggested Job Role\"].unique() \n",
        "Y = pd.DataFrame({'Suggested Job Role':original, 'Associated Number':numeric})"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i2x9-61AiYPx",
        "outputId": "67e805d6-aa36-4ee8-e220-3714849964a9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "Y"
      ],
      "execution_count": 9,
      "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>Suggested Job Role</th>\n",
              "      <th>Associated Number</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Database Developer</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Portal Administrator</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Systems Security Administrator</td>\n",
              "      <td>28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Business Systems Analyst</td>\n",
              "      <td>2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Software Systems Engineer</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Business Intelligence Analyst</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>CRM Technical Developer</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Mobile Applications Developer</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>UX Designer</td>\n",
              "      <td>32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Quality Assurance Associate</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Web Developer</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Information Security Analyst</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>CRM Business Analyst</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Technical Support</td>\n",
              "      <td>31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Project Manager</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Information Technology Manager</td>\n",
              "      <td>13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Programmer Analyst</td>\n",
              "      <td>19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>Design &amp; UX</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>Solutions Architect</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Systems Analyst</td>\n",
              "      <td>27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Network Security Administrator</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>Data Architect</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>Software Developer</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>E-Commerce Analyst</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>Technical Services/Help Desk/Tech Support</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>Information Technology Auditor</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>Database Manager</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>Applications Developer</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Database Administrator</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>Network Engineer</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>Software Engineer</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>Technical Engineer</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>Network Security Engineer</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>Software Quality Assurance (QA) / Testing</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                           Suggested Job Role  Associated Number\n",
              "0                          Database Developer                  7\n",
              "1                        Portal Administrator                 18\n",
              "2              Systems Security Administrator                 28\n",
              "3                    Business Systems Analyst                  2\n",
              "4                   Software Systems Engineer                 25\n",
              "5               Business Intelligence Analyst                  1\n",
              "6                     CRM Technical Developer                  4\n",
              "7               Mobile Applications Developer                 14\n",
              "8                                 UX Designer                 32\n",
              "9                 Quality Assurance Associate                 21\n",
              "10                              Web Developer                 33\n",
              "11               Information Security Analyst                 11\n",
              "12                       CRM Business Analyst                  3\n",
              "13                          Technical Support                 31\n",
              "14                            Project Manager                 20\n",
              "15             Information Technology Manager                 13\n",
              "16                         Programmer Analyst                 19\n",
              "17                                Design & UX                  9\n",
              "18                        Solutions Architect                 26\n",
              "19                            Systems Analyst                 27\n",
              "20             Network Security Administrator                 16\n",
              "21                             Data Architect                  5\n",
              "22                         Software Developer                 22\n",
              "23                         E-Commerce Analyst                 10\n",
              "24  Technical Services/Help Desk/Tech Support                 30\n",
              "25             Information Technology Auditor                 12\n",
              "26                           Database Manager                  8\n",
              "27                     Applications Developer                  0\n",
              "28                     Database Administrator                  6\n",
              "29                           Network Engineer                 15\n",
              "30                          Software Engineer                 23\n",
              "31                         Technical Engineer                 29\n",
              "32                  Network Security Engineer                 17\n",
              "33  Software Quality Assurance (QA) / Testing                 24"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "J6CsfRUlCP81"
      },
      "source": [
        "# Decision Tree"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZBNW8YEKCP82"
      },
      "source": [
        "Dependent Variable: Categorical \n",
        "    \n",
        "Independent Variable : Categorical and Continous\n",
        "    \n",
        "Used to classify records in a pictorial format with the help of gini index"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BrAzyuvKCP82"
      },
      "source": [
        "Random Forest Technique is used to find the accuracy and important features to be used while implementing Decision Tree."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k9-vdHdhCP86",
        "outputId": "376f4c6c-bab9-44de-d617-1514c3c2a4fb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from sklearn.ensemble import RandomForestClassifier\n",
        "rf_model=RandomForestClassifier(n_estimators=1000,max_features=2,oob_score=True)\n",
        "X=dataset.copy()\n",
        "rf_model.fit(X,df['Suggested Job Role'])\n",
        "print(\"OOB Accuracy\")\n",
        "print(rf_model.oob_score_)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "OOB Accuracy\n",
            "0.0421\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pryj7SvfEOgv",
        "outputId": "05faad30-3bef-4e57-8f9e-d0d13f2b2c25",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "feature = X.columns\n",
        "imp=np.empty(len(feature))\n",
        "i=0\n",
        "for feat,imp_val in zip(feature,rf_model.feature_importances_):\n",
        "    #print(feature,imp)\n",
        "    imp[i]=imp_val\n",
        "    i=i+1\n",
        "\n",
        "indices = np.argsort(imp)\n",
        "\n",
        "for i in indices:\n",
        "    print(feature[i],imp[i])\n"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Taken inputs from seniors or elders 0.012526986674559988\n",
            "hard/smart worker 0.012734631992113454\n",
            "In a Realtionship? 0.012824434488487801\n",
            "Management or Technical 0.012827947629580332\n",
            "Salary Range Expected 0.012958493035120259\n",
            "worked in teams ever? 0.01303247540274887\n",
            "self-learning capability? 0.01311479268535878\n",
            "interested in games 0.013123312181191716\n",
            "Salary/work 0.013211947336152321\n",
            "talenttests taken? 0.013214312295705508\n",
            "Introvert 0.013221418778646124\n",
            "Job/Higher Studies? 0.01328394039125629\n",
            "Gentle or Tuff behaviour? 0.01333644359895035\n",
            "can work long time before system? 0.013355266346676697\n",
            "Extra-courses did 0.013384398005023649\n",
            "olympiads 0.013448500357625705\n",
            "reading and writing skills 0.019656469742627324\n",
            "memory capability score 0.020037193318279814\n",
            "interested career area  0.027719514860610424\n",
            "workshops 0.030367007270364437\n",
            "certifications 0.031151481293306672\n",
            "Type of company want to settle in? 0.03184363278210286\n",
            "Interested subjects 0.03186878240545834\n",
            "Interested Type of Books 0.03687262746149775\n",
            "hackathons 0.038349919809118914\n",
            "Percentage in Communication skills 0.04009488541258666\n",
            "percentage in Algorithms 0.04009770638571768\n",
            "Percentage in Software Engineering 0.04011667231276528\n",
            "Percentage in Programming Concepts 0.040127942532819844\n",
            "Hours working per day 0.04016632806607123\n",
            "Percentage in Computer Architecture 0.0401727028067794\n",
            "Percentage in Computer Networks 0.040191254031678426\n",
            "coding skills rating 0.04021605229336121\n",
            "Percentage in Mathematics 0.04022070081132897\n",
            "public speaking points 0.04023084033446955\n",
            "Acedamic percentage in Operating Systems 0.04024572719220061\n",
            "Logical quotient rating 0.04025650181745674\n",
            "Percentage in Electronics Subjects 0.040396755860200154\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z_BqCRZ-obgo"
      },
      "source": [
        "Since all values are almost close, we can not eliminate any one of the features."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IfziUQfPod6Z"
      },
      "source": [
        "#Decision Tree Classifier\n",
        "\n",
        "from sklearn import tree\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn import preprocessing \n",
        "from sklearn.metrics import accuracy_score"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pMmfjJ6Pop8-"
      },
      "source": [
        "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=10)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RRCA90kuo-jD",
        "outputId": "68818e90-9626-4dcd-9b25-691a57520666",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "DT_model = tree.DecisionTreeClassifier()\n",
        "DT_model = DT_model.fit(X_train, y_train)\n",
        "DT_model"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',\n",
              "                       max_depth=None, max_features=None, max_leaf_nodes=None,\n",
              "                       min_impurity_decrease=0.0, min_impurity_split=None,\n",
              "                       min_samples_leaf=1, min_samples_split=2,\n",
              "                       min_weight_fraction_leaf=0.0, presort='deprecated',\n",
              "                       random_state=None, splitter='best')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aaoO4WcypUHn"
      },
      "source": [
        "#Generate Decision Tree Graph\n",
        "features=['Acedamic percentage in Operating Systems', 'percentage in Algorithms',\n",
        "       'Percentage in Programming Concepts',\n",
        "       'Percentage in Software Engineering', 'Percentage in Computer Networks',\n",
        "       'Percentage in Electronics Subjects',\n",
        "       'Percentage in Computer Architecture', 'Percentage in Mathematics',\n",
        "       'Percentage in Communication skills', 'Hours working per day',\n",
        "       'Logical quotient rating', 'hackathons', 'coding skills rating',\n",
        "       'public speaking points', 'can work long time before system?',\n",
        "       'self-learning capability?', 'Extra-courses did', 'certifications',\n",
        "       'workshops', 'talenttests taken?', 'olympiads',\n",
        "       'reading and writing skills', 'memory capability score',\n",
        "       'Interested subjects', 'interested career area ', 'Job/Higher Studies?',\n",
        "       'Type of company want to settle in?',\n",
        "       'Taken inputs from seniors or elders', 'interested in games',\n",
        "       'Interested Type of Books', 'Salary Range Expected',\n",
        "       'In a Realtionship?', 'Gentle or Tuff behaviour?',\n",
        "       'Management or Technical', 'Salary/work', 'hard/smart worker',\n",
        "       'worked in teams ever?', 'Introvert']\n",
        "with open('Dtree3.dot','w') as f:\n",
        "    f=tree.export_graphviz(DT_model,feature_names=features,out_file=f)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q8jwGLcvsiwZ",
        "outputId": "16d0b593-c5c1-4f66-b895-c6d5a48eec69",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "r=tree.export_text(DT_model,feature_names=features)\n",
        "print(r)"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "|--- Percentage in Electronics Subjects <= 0.44\n",
            "|   |--- percentage in Algorithms <= 0.44\n",
            "|   |   |--- percentage in Algorithms <= 0.44\n",
            "|   |   |   |--- Acedamic percentage in Operating Systems <= 0.44\n",
            "|   |   |   |   |--- coding skills rating <= 0.04\n",
            "|   |   |   |   |   |--- percentage in Algorithms <= 0.39\n",
            "|   |   |   |   |   |   |--- public speaking points <= 0.04\n",
            "|   |   |   |   |   |   |   |--- Percentage in Electronics Subjects <= 0.31\n",
            "|   |   |   |   |   |   |   |   |--- Logical quotient rating <= 0.00\n",
            "|   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems <= 0.37\n",
            "|   |   |   |   |   |   |   |   |   |   |--- public speaking points <= 0.04\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12\n",
            "|   |   |   |   |   |   |   |   |   |   |--- public speaking points >  0.04\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 14\n",
            "|   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems >  0.37\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day <= 0.03\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day >  0.03\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 22\n",
            "|   |   |   |   |   |   |   |   |--- Logical quotient rating >  0.00\n",
            "|   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems <= 0.24\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 28\n",
            "|   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems >  0.24\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day <= 0.03\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 35\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day >  0.03\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 33\n",
            "|   |   |   |   |   |   |   |--- Percentage in Electronics Subjects >  0.31\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering <= 0.41\n",
            "|   |   |   |   |   |   |   |   |   |--- percentage in Algorithms <= 0.39\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Software Engineering <= 0.41\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 49\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Software Engineering >  0.41\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4\n",
            "|   |   |   |   |   |   |   |   |   |--- percentage in Algorithms >  0.39\n",
            "|   |   |   |   |   |   |   |   |   |   |--- interested career area  <= 0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4\n",
            "|   |   |   |   |   |   |   |   |   |   |--- interested career area  >  0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering >  0.41\n",
            "|   |   |   |   |   |   |   |   |   |--- percentage in Algorithms <= 0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Interested Type of Books <= 9.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Interested Type of Books >  9.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10\n",
            "|   |   |   |   |   |   |   |   |   |--- percentage in Algorithms >  0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |--- workshops <= 2.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2\n",
            "|   |   |   |   |   |   |   |   |   |   |--- workshops >  2.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 8\n",
            "|   |   |   |   |   |   |--- public speaking points >  0.04\n",
            "|   |   |   |   |   |   |   |--- Percentage in Software Engineering <= 0.35\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts <= 0.25\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Mathematics <= 0.33\n",
            "|   |   |   |   |   |   |   |   |   |   |--- olympiads <= 0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 9\n",
            "|   |   |   |   |   |   |   |   |   |   |--- olympiads >  0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 21\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Mathematics >  0.33\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 26\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts >  0.25\n",
            "|   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems <= 0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |--- hard/smart worker <= 0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 18\n",
            "|   |   |   |   |   |   |   |   |   |   |--- hard/smart worker >  0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 19\n",
            "|   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems >  0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Mathematics <= 0.42\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 25\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Mathematics >  0.42\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 10\n",
            "|   |   |   |   |   |   |   |--- Percentage in Software Engineering >  0.35\n",
            "|   |   |   |   |   |   |   |   |--- Hours working per day <= 0.02\n",
            "|   |   |   |   |   |   |   |   |   |--- Logical quotient rating <= 0.01\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 6\n",
            "|   |   |   |   |   |   |   |   |   |--- Logical quotient rating >  0.01\n",
            "|   |   |   |   |   |   |   |   |   |   |--- coding skills rating <= 0.01\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 7\n",
            "|   |   |   |   |   |   |   |   |   |   |--- coding skills rating >  0.01\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 21\n",
            "|   |   |   |   |   |   |   |   |--- Hours working per day >  0.02\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Electronics Subjects <= 0.38\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems <= 0.40\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 25\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems >  0.40\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Electronics Subjects >  0.38\n",
            "|   |   |   |   |   |   |   |   |   |   |--- coding skills rating <= 0.04\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10\n",
            "|   |   |   |   |   |   |   |   |   |   |--- coding skills rating >  0.04\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 22\n",
            "|   |   |   |   |   |--- percentage in Algorithms >  0.39\n",
            "|   |   |   |   |   |   |--- percentage in Algorithms <= 0.40\n",
            "|   |   |   |   |   |   |   |--- coding skills rating <= 0.01\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering <= 0.27\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 30\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.40\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.40\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 30\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering >  0.27\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Computer Architecture <= 0.36\n",
            "|   |   |   |   |   |   |   |   |   |   |--- workshops <= 4.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 10\n",
            "|   |   |   |   |   |   |   |   |   |   |--- workshops >  4.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Computer Architecture >  0.36\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Type of company want to settle in? <= 5.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Type of company want to settle in? >  5.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |   |   |--- coding skills rating >  0.01\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Communication skills <= 0.29\n",
            "|   |   |   |   |   |   |   |   |   |--- coding skills rating <= 0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts <= 0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 8\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts >  0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |   |   |   |   |--- coding skills rating >  0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |--- hackathons <= 0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 13\n",
            "|   |   |   |   |   |   |   |   |   |   |--- hackathons >  0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Communication skills >  0.29\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts <= 0.41\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Architecture <= 0.41\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 17\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Architecture >  0.41\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 32\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts >  0.41\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 21\n",
            "|   |   |   |   |   |   |--- percentage in Algorithms >  0.40\n",
            "|   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.27\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering <= 0.31\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts <= 0.30\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 17\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts >  0.30\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Interested Type of Books <= 17.00\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 25\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Interested Type of Books >  17.00\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering >  0.31\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Mathematics <= 0.37\n",
            "|   |   |   |   |   |   |   |   |   |   |--- hackathons <= 0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6\n",
            "|   |   |   |   |   |   |   |   |   |   |--- hackathons >  0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 3\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Mathematics >  0.37\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 7\n",
            "|   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.27\n",
            "|   |   |   |   |   |   |   |   |--- Logical quotient rating <= 0.00\n",
            "|   |   |   |   |   |   |   |   |   |--- interested career area  <= 3.50\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.38\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 12\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.38\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 2\n",
            "|   |   |   |   |   |   |   |   |   |--- interested career area  >  3.50\n",
            "|   |   |   |   |   |   |   |   |   |   |--- workshops <= 5.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2\n",
            "|   |   |   |   |   |   |   |   |   |   |--- workshops >  5.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4\n",
            "|   |   |   |   |   |   |   |   |--- Logical quotient rating >  0.00\n",
            "|   |   |   |   |   |   |   |   |   |--- Logical quotient rating <= 0.01\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Architecture <= 0.32\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Architecture >  0.32\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 30\n",
            "|   |   |   |   |   |   |   |   |   |--- Logical quotient rating >  0.01\n",
            "|   |   |   |   |   |   |   |   |   |   |--- coding skills rating <= 0.00\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 5\n",
            "|   |   |   |   |   |   |   |   |   |   |--- coding skills rating >  0.00\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 17\n",
            "|   |   |   |   |--- coding skills rating >  0.04\n",
            "|   |   |   |   |   |--- Percentage in Electronics Subjects <= 0.42\n",
            "|   |   |   |   |   |   |--- Percentage in Computer Architecture <= 0.34\n",
            "|   |   |   |   |   |   |   |--- coding skills rating <= 0.04\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.41\n",
            "|   |   |   |   |   |   |   |   |   |--- class: 3\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.41\n",
            "|   |   |   |   |   |   |   |   |   |--- class: 11\n",
            "|   |   |   |   |   |   |   |--- coding skills rating >  0.04\n",
            "|   |   |   |   |   |   |   |   |--- coding skills rating <= 0.04\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts <= 0.33\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day <= 0.05\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 11\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day >  0.05\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Programming Concepts >  0.33\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Interested subjects <= 5.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 14\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Interested subjects >  5.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 9\n",
            "|   |   |   |   |   |   |   |   |--- coding skills rating >  0.04\n",
            "|   |   |   |   |   |   |   |   |   |--- percentage in Algorithms <= 0.31\n",
            "|   |   |   |   |   |   |   |   |   |   |--- reading and writing skills <= 1.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |   |   |   |   |   |--- reading and writing skills >  1.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 8\n",
            "|   |   |   |   |   |   |   |   |   |--- percentage in Algorithms >  0.31\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.42\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.42\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 26\n",
            "|   |   |   |   |   |   |--- Percentage in Computer Architecture >  0.34\n",
            "|   |   |   |   |   |   |   |--- Salary Range Expected <= 0.50\n",
            "|   |   |   |   |   |   |   |   |--- coding skills rating <= 0.04\n",
            "|   |   |   |   |   |   |   |   |   |--- Interested Type of Books <= 20.50\n",
            "|   |   |   |   |   |   |   |   |   |   |--- reading and writing skills <= 1.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2\n",
            "|   |   |   |   |   |   |   |   |   |   |--- reading and writing skills >  1.50\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 33\n",
            "|   |   |   |   |   |   |   |   |   |--- Interested Type of Books >  20.50\n",
            "|   |   |   |   |   |   |   |   |   |   |--- class: 23\n",
            "|   |   |   |   |   |   |   |   |--- coding skills rating >  0.04\n",
            "|   |   |   |   |   |   |   |   |   |--- memory capability score <= 0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |--- public speaking points <= 0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 2\n",
            "|   |   |   |   |   |   |   |   |   |   |--- public speaking points >  0.02\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4\n",
            "|   |   |   |   |   |   |   |   |   |--- memory capability score >  0.50\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day <= 0.06\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Hours working per day >  0.06\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- class: 28\n",
            "|   |   |   |   |   |   |   |--- Salary Range Expected >  0.50\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering <= 0.28\n",
            "|   |   |   |   |   |   |   |   |   |--- class: 29\n",
            "|   |   |   |   |   |   |   |   |--- Percentage in Software Engineering >  0.28\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks <= 0.33\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems <= 0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 4\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Acedamic percentage in Operating Systems >  0.34\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 7\n",
            "|   |   |   |   |   |   |   |   |   |--- Percentage in Computer Networks >  0.33\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Communication skills <= 0.30\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 6\n",
            "|   |   |   |   |   |   |   |   |   |   |--- Percentage in Communication skills >  0.30\n",
            "|   |   |   |   |   |   |   |   |   |   |   |--- truncated branch of depth 3\n",
            "|   |   |   |   |   |--- Percentage in Electronics Subjects >  0.42\n",
            "|   |   |   |   |   |   |--- Interested Type of Books <= 20.50\n",
            "|   |   |   |   |   |   |   |--- class: 3\n",
            "|   |   |   |   |   |   |--- Interested Type of Books >  20.50\n",
            "|   |   |   |   |   |   |   |--- class: 30\n",
            "|   |   |   |--- Acedamic percentage in Operating Systems >  0.44\n",
            "|   |   |   |   |--- class: 33\n",
            "|   |   |--- percentage in Algorithms >  0.44\n",
            "|   |   |   |--- class: 25\n",
            "|   |--- percentage in Algorithms >  0.44\n",
            "|   |   |--- class: 1\n",
            "|--- Percentage in Electronics Subjects >  0.44\n",
            "|   |--- Percentage in Programming Concepts <= 0.30\n",
            "|   |   |--- class: 26\n",
            "|   |--- Percentage in Programming Concepts >  0.30\n",
            "|   |   |--- public speaking points <= 0.04\n",
            "|   |   |   |--- class: 1\n",
            "|   |   |--- public speaking points >  0.04\n",
            "|   |   |   |--- class: 0\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QomdGXuw0MXT",
        "outputId": "cbd7a7fb-43e1-439e-e5d5-a9664e1ff792",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "source": [
        "# Prediction\n",
        "y_pred = DT_model.predict(X_test)\n",
        "y_test_arr=y_test['Suggested Job Role']\n",
        "Final = pd.DataFrame({'Predicted':y_pred, 'Actual':y_test_arr})\n",
        "Final.reset_index()"
      ],
      "execution_count": 17,
      "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>index</th>\n",
              "      <th>Predicted</th>\n",
              "      <th>Actual</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>19778</td>\n",
              "      <td>14</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4376</td>\n",
              "      <td>6</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>10188</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9887</td>\n",
              "      <td>18</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4441</td>\n",
              "      <td>5</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3995</th>\n",
              "      <td>13123</td>\n",
              "      <td>13</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3996</th>\n",
              "      <td>18706</td>\n",
              "      <td>12</td>\n",
              "      <td>17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3997</th>\n",
              "      <td>7274</td>\n",
              "      <td>14</td>\n",
              "      <td>25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3998</th>\n",
              "      <td>16155</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3999</th>\n",
              "      <td>16712</td>\n",
              "      <td>28</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4000 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      index  Predicted  Actual\n",
              "0     19778         14      24\n",
              "1      4376          6      24\n",
              "2     10188          6      10\n",
              "3      9887         18       5\n",
              "4      4441          5       9\n",
              "...     ...        ...     ...\n",
              "3995  13123         13      20\n",
              "3996  18706         12      17\n",
              "3997   7274         14      25\n",
              "3998  16155          3       0\n",
              "3999  16712         28      26\n",
              "\n",
              "[4000 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R-F1E35f0WYC",
        "outputId": "a4d328c4-d9df-47c1-e2a5-c84ea672a515",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from sklearn.metrics import accuracy_score\n",
        "accuracy = accuracy_score(y_test,y_pred)\n",
        "print(\"accuracy=\",accuracy*100)"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "accuracy= 2.9250000000000003\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_OF62f6H-6t8",
        "outputId": "8dcb748d-8938-4774-fd9b-e97f1907428b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "#Number of correct predicted\n",
        "comparison_column = np.where(Final['Predicted'] == Final['Actual'], 1, 0)\n",
        "Number_of_correct_predictions=list(comparison_column).count(1)\n",
        "print(\"Number_of_correct_predictions : \",((Number_of_correct_predictions)/4000)*100,\"%\")\n",
        "accuracy_DT=Number_of_correct_predictions"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Number_of_correct_predictions :  2.9250000000000003 %\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7w1VFpPRFjN4",
        "outputId": "2843379d-7773-4310-ffbf-955590077580",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "y_train=y_train['Suggested Job Role']\n",
        "y_train"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "18660    16\n",
              "10831     4\n",
              "5511     28\n",
              "3543     11\n",
              "12340     3\n",
              "         ..\n",
              "9372     31\n",
              "7291     19\n",
              "17728     5\n",
              "7293      6\n",
              "17673    31\n",
              "Name: Suggested Job Role, Length: 16000, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "APujDEJH4cRV"
      },
      "source": [
        "# Support Vector Machine"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6zm-K_Wg4fpN",
        "outputId": "fa1191e0-8559-4fd5-9c4d-76fe68d7433a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "# Run svm with default hyper parameters\n",
        "# Default hyperparameter means C=1.0, kernel=rbf and gamma=auto among other parameters\n",
        "# import SVC classifier\n",
        "from sklearn.svm import SVC\n",
        "\n",
        "# import metrics to compute accuracy\n",
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "# instantiate classifier with default hyperparameters\n",
        "svc=SVC() \n",
        "\n",
        "# fit classifier to training set\n",
        "svc.fit(X_train,y_train)\n",
        "\n",
        "# make predictions on test set\n",
        "y_pred=svc.predict(X_test)\n",
        "\n",
        "\n",
        "# compute and print accuracy score\n",
        "print('Model accuracy score with default hyperparameters: {0:0.4f}'. format(accuracy_score(y_test, y_pred)*100))"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model accuracy score with default hyperparameters: 5.6000\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2n9tuEpxCEcS"
      },
      "source": [
        "# Run svm with default hyper parameters\n",
        "# Default hyperparameter means C=1.0, kernel=linear and gamma=auto among other parameters\n",
        "# import SVC classifier\n",
        "from sklearn.svm import SVC\n",
        "\n",
        "# import metrics to compute accuracy\n",
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "# instantiate classifier with default hyperparameters\n",
        "svc=SVC(kernel='linear') \n",
        "\n",
        "# fit classifier to training set\n",
        "svc.fit(X_train,y_train)\n",
        "\n",
        "# make predictions on test set\n",
        "y_pred=svc.predict(X_test)\n",
        "\n",
        "\n",
        "# compute and print accuracy score\n",
        "print('Model accuracy score with default hyperparameters: {0:0.4f}'. format(accuracy_score(y_test, y_pred)))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N7t3gtexPs0i"
      },
      "source": [
        "# XGBOOST"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9SCAcfeCPsAy",
        "outputId": "c007cf08-69bd-4d3e-c84f-0e27e8cf07c4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from numpy import loadtxt\n",
        "from xgboost import XGBClassifier\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score\n",
        "\n",
        "import pandas as pd\n",
        "X_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.2,random_state=10)\n",
        "\n",
        "X_train=pd.to_numeric(X_train.values.flatten())\n",
        "X_train=X_train.reshape((16000,38))\n",
        "X_test=pd.to_numeric(X_test.values.flatten())\n",
        "X_test=X_test.reshape((4000,38))\n",
        "\n",
        "# fit model no training data\n",
        "model = XGBClassifier()\n",
        "model.fit(X_train, y_train['Suggested Job Role'])\n"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
              "              colsample_bynode=1, colsample_bytree=1, gamma=0,\n",
              "              learning_rate=0.1, max_delta_step=0, max_depth=3,\n",
              "              min_child_weight=1, missing=None, n_estimators=100, n_jobs=1,\n",
              "              nthread=None, objective='multi:softprob', random_state=0,\n",
              "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=None,\n",
              "              silent=None, subsample=1, verbosity=1)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fhohefplcyBE",
        "outputId": "2d9c5136-985f-4cc5-f5ee-7f097eb434b4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "y_pred = model.predict(X_test)\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "print(accuracy)"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "0.0425\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M22rLICN9CZx",
        "outputId": "a1831e8b-6e0e-46a2-d964-6d7601689e6d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        }
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "fig = plt.figure()\n",
        "ax = fig.add_axes([0,0,1,1])\n",
        "Name = ['Decision Tree', 'SVM', 'XGBoost']\n",
        "accuracies = [2.925,5.6,4.25]\n",
        "ax.bar(Name,accuracies)\n",
        "ax.set_ylabel('Accuracies')\n",
        "ax.set_xlabel('Techniques')\n",
        "plt.show()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "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": "markdown",
      "metadata": {
        "id": "3VTK6Vku937X"
      },
      "source": [
        "So, SVM has highest Accuuracy and hence is best suited."
      ]
    }
  ]
}