Visual.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x2b733d0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = pd.read_csv('data.csv', sep=' ', header=None)\n",
    "pos = data[data[2]==1]\n",
    "neg = data[data[2]==0]\n",
    "plt.scatter(pos[0], pos[1])\n",
    "plt.scatter(neg[0], neg[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x6f531b0>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "threshold = 0.35\n",
    "data = pd.read_csv('result.csv', sep=' ', header=None)\n",
    "pos = data[data[2]>=threshold]\n",
    "neg = data[data[2]<threshold]\n",
    "plt.scatter(pos[0], pos[1])\n",
    "plt.scatter(neg[0], neg[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7.708334</td>\n",
       "      <td>5.258933</td>\n",
       "      <td>0.226715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.599180</td>\n",
       "      <td>7.785779</td>\n",
       "      <td>0.007130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.666935</td>\n",
       "      <td>1.901367</td>\n",
       "      <td>0.543430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.439344</td>\n",
       "      <td>8.502351</td>\n",
       "      <td>0.005019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>9.035657</td>\n",
       "      <td>6.686271</td>\n",
       "      <td>0.151148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>9.482100</td>\n",
       "      <td>6.243899</td>\n",
       "      <td>0.168269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5.790678</td>\n",
       "      <td>7.628460</td>\n",
       "      <td>0.010398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1.056117</td>\n",
       "      <td>4.825252</td>\n",
       "      <td>0.031707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.459923</td>\n",
       "      <td>4.481119</td>\n",
       "      <td>0.040858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.912123</td>\n",
       "      <td>4.639076</td>\n",
       "      <td>0.034694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>8.900339</td>\n",
       "      <td>0.412412</td>\n",
       "      <td>0.788413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3.581978</td>\n",
       "      <td>4.517340</td>\n",
       "      <td>0.053563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>9.566909</td>\n",
       "      <td>7.876234</td>\n",
       "      <td>0.110569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>9.551316</td>\n",
       "      <td>9.596900</td>\n",
       "      <td>0.064658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.971068</td>\n",
       "      <td>6.528905</td>\n",
       "      <td>0.011180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3.827101</td>\n",
       "      <td>5.538225</td>\n",
       "      <td>0.029708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2.885925</td>\n",
       "      <td>7.651860</td>\n",
       "      <td>0.007087</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7.941368</td>\n",
       "      <td>1.166168</td>\n",
       "      <td>0.682801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>3.387538</td>\n",
       "      <td>6.204096</td>\n",
       "      <td>0.018698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.662004</td>\n",
       "      <td>1.779818</td>\n",
       "      <td>0.148391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9.594364</td>\n",
       "      <td>7.503699</td>\n",
       "      <td>0.120874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>6.820100</td>\n",
       "      <td>0.559574</td>\n",
       "      <td>0.746230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.036940</td>\n",
       "      <td>6.890751</td>\n",
       "      <td>0.007902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4.007605</td>\n",
       "      <td>5.602853</td>\n",
       "      <td>0.029244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.099752</td>\n",
       "      <td>1.979074</td>\n",
       "      <td>0.144470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>5.582998</td>\n",
       "      <td>7.325319</td>\n",
       "      <td>0.012277</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>5.459380</td>\n",
       "      <td>1.540060</td>\n",
       "      <td>0.603398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>5.061430</td>\n",
       "      <td>0.613236</td>\n",
       "      <td>0.719992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>4.682833</td>\n",
       "      <td>2.478011</td>\n",
       "      <td>0.478161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.554812</td>\n",
       "      <td>1.943437</td>\n",
       "      <td>0.136331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>6.900587</td>\n",
       "      <td>1.636754</td>\n",
       "      <td>0.605464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2.511477</td>\n",
       "      <td>3.800646</td>\n",
       "      <td>0.068778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>1.177564</td>\n",
       "      <td>2.004187</td>\n",
       "      <td>0.144790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>4.895998</td>\n",
       "      <td>7.957844</td>\n",
       "      <td>0.007531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2.382827</td>\n",
       "      <td>4.357201</td>\n",
       "      <td>0.049456</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>7.637614</td>\n",
       "      <td>6.045008</td>\n",
       "      <td>0.184735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>6.616884</td>\n",
       "      <td>7.684489</td>\n",
       "      <td>0.011509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>5.132101</td>\n",
       "      <td>8.238929</td>\n",
       "      <td>0.006483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>4.123067</td>\n",
       "      <td>4.254604</td>\n",
       "      <td>0.186924</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>8.013618</td>\n",
       "      <td>4.892256</td>\n",
       "      <td>0.250252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>0.438009</td>\n",
       "      <td>5.090251</td>\n",
       "      <td>0.024982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>6.641792</td>\n",
       "      <td>6.968707</td>\n",
       "      <td>0.060397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>4.084734</td>\n",
       "      <td>1.149925</td>\n",
       "      <td>0.642151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2.510240</td>\n",
       "      <td>8.696192</td>\n",
       "      <td>0.003474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>6.304601</td>\n",
       "      <td>2.867632</td>\n",
       "      <td>0.439446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>4.601119</td>\n",
       "      <td>0.774504</td>\n",
       "      <td>0.695103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>3.617904</td>\n",
       "      <td>5.633684</td>\n",
       "      <td>0.027296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>9.854610</td>\n",
       "      <td>2.957471</td>\n",
       "      <td>0.457274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>8.317829</td>\n",
       "      <td>9.329626</td>\n",
       "      <td>0.005299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>0.808688</td>\n",
       "      <td>2.943392</td>\n",
       "      <td>0.087230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>5.022876</td>\n",
       "      <td>3.414585</td>\n",
       "      <td>0.377453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>6.493439</td>\n",
       "      <td>4.675490</td>\n",
       "      <td>0.269014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>6.123027</td>\n",
       "      <td>9.391638</td>\n",
       "      <td>0.003491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>0.238465</td>\n",
       "      <td>0.915971</td>\n",
       "      <td>0.201625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>4.634607</td>\n",
       "      <td>3.444709</td>\n",
       "      <td>0.374744</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>6.338647</td>\n",
       "      <td>1.215206</td>\n",
       "      <td>0.656345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>3.635917</td>\n",
       "      <td>4.324945</td>\n",
       "      <td>0.064270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>6.278297</td>\n",
       "      <td>8.833831</td>\n",
       "      <td>0.005105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>5.407706</td>\n",
       "      <td>4.079718</td>\n",
       "      <td>0.317444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2.115044</td>\n",
       "      <td>4.161194</td>\n",
       "      <td>0.053412</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           0         1         2\n",
       "0   7.708334  5.258933  0.226715\n",
       "1   3.599180  7.785779  0.007130\n",
       "2   3.666935  1.901367  0.543430\n",
       "3   4.439344  8.502351  0.005019\n",
       "4   9.035657  6.686271  0.151148\n",
       "5   9.482100  6.243899  0.168269\n",
       "6   5.790678  7.628460  0.010398\n",
       "7   1.056117  4.825252  0.031707\n",
       "8   1.459923  4.481119  0.040858\n",
       "9   0.912123  4.639076  0.034694\n",
       "10  8.900339  0.412412  0.788413\n",
       "11  3.581978  4.517340  0.053563\n",
       "12  9.566909  7.876234  0.110569\n",
       "13  9.551316  9.596900  0.064658\n",
       "14  0.971068  6.528905  0.011180\n",
       "15  3.827101  5.538225  0.029708\n",
       "16  2.885925  7.651860  0.007087\n",
       "17  7.941368  1.166168  0.682801\n",
       "18  3.387538  6.204096  0.018698\n",
       "19  0.662004  1.779818  0.148391\n",
       "20  9.594364  7.503699  0.120874\n",
       "21  6.820100  0.559574  0.746230\n",
       "22  0.036940  6.890751  0.007902\n",
       "23  4.007605  5.602853  0.029244\n",
       "24  1.099752  1.979074  0.144470\n",
       "25  5.582998  7.325319  0.012277\n",
       "26  5.459380  1.540060  0.603398\n",
       "27  5.061430  0.613236  0.719992\n",
       "28  4.682833  2.478011  0.478161\n",
       "29  0.554812  1.943437  0.136331\n",
       "..       ...       ...       ...\n",
       "70  6.900587  1.636754  0.605464\n",
       "71  2.511477  3.800646  0.068778\n",
       "72  1.177564  2.004187  0.144790\n",
       "73  4.895998  7.957844  0.007531\n",
       "74  2.382827  4.357201  0.049456\n",
       "75  7.637614  6.045008  0.184735\n",
       "76  6.616884  7.684489  0.011509\n",
       "77  5.132101  8.238929  0.006483\n",
       "78  4.123067  4.254604  0.186924\n",
       "79  8.013618  4.892256  0.250252\n",
       "80  0.438009  5.090251  0.024982\n",
       "81  6.641792  6.968707  0.060397\n",
       "82  4.084734  1.149925  0.642151\n",
       "83  2.510240  8.696192  0.003474\n",
       "84  6.304601  2.867632  0.439446\n",
       "85  4.601119  0.774504  0.695103\n",
       "86  3.617904  5.633684  0.027296\n",
       "87  9.854610  2.957471  0.457274\n",
       "88  8.317829  9.329626  0.005299\n",
       "89  0.808688  2.943392  0.087230\n",
       "90  5.022876  3.414585  0.377453\n",
       "91  6.493439  4.675490  0.269014\n",
       "92  6.123027  9.391638  0.003491\n",
       "93  0.238465  0.915971  0.201625\n",
       "94  4.634607  3.444709  0.374744\n",
       "95  6.338647  1.215206  0.656345\n",
       "96  3.635917  4.324945  0.064270\n",
       "97  6.278297  8.833831  0.005105\n",
       "98  5.407706  4.079718  0.317444\n",
       "99  2.115044  4.161194  0.053412\n",
       "\n",
       "[100 rows x 3 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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