Amazon Data Science Q2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import cv2\n",
    "import pandas as pd\n",
    "import glob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Andesite_data shape: (5000, 28, 28, 3)\n"
     ]
    }
   ],
   "source": [
    "andesite_data = []\n",
    "files = glob.glob (\"C:/Users/KIIT/Downloads/geological_similarity/andesite/*.jpg\")\n",
    "for myFile in files:\n",
    "    image = cv2.imread (myFile)\n",
    "    andesite_data.append (image)\n",
    "\n",
    "print('Andesite_data shape:', np.array(andesite_data).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gneiss_data shape: (5000, 28, 28, 3)\n"
     ]
    }
   ],
   "source": [
    "gneiss_data = []\n",
    "files = glob.glob (\"C:/Users/KIIT/Downloads/geological_similarity/gneiss/*.jpg\")\n",
    "for myFile in files:\n",
    "    image = cv2.imread (myFile)\n",
    "    gneiss_data.append (image)\n",
    "\n",
    "print('gneiss_data shape:', np.array(gneiss_data).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "marble_data shape: (4998, 28, 28, 3)\n"
     ]
    }
   ],
   "source": [
    "marble_data = []\n",
    "files = glob.glob (\"C:/Users/KIIT/Downloads/geological_similarity/marble/*.jpg\")\n",
    "for myFile in files:\n",
    "    image = cv2.imread (myFile)\n",
    "    marble_data.append (image)\n",
    "\n",
    "print('marble_data shape:', np.array(marble_data).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "marble_data shape: (5000, 28, 28, 3)\n"
     ]
    }
   ],
   "source": [
    "quartzite_data = []\n",
    "files = glob.glob (\"C:/Users/KIIT/Downloads/geological_similarity/quartzite/*.jpg\")\n",
    "for myFile in files:\n",
    "    image = cv2.imread (myFile)\n",
    "    quartzite_data.append (image)\n",
    "\n",
    "print('marble_data shape:', np.array(quartzite_data).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rhyolite_data shape: (5000, 28, 28, 3)\n"
     ]
    }
   ],
   "source": [
    "rhyolite_data = []\n",
    "files = glob.glob (\"C:/Users/KIIT/Downloads/geological_similarity/rhyolite/*.jpg\")\n",
    "for myFile in files:\n",
    "    image = cv2.imread (myFile)\n",
    "    rhyolite_data.append (image)\n",
    "\n",
    "print('rhyolite_data shape:', np.array(rhyolite_data).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "schist_data shape: (5000, 28, 28, 3)\n"
     ]
    }
   ],
   "source": [
    "schist_data = []\n",
    "files = glob.glob (\"C:/Users/KIIT/Downloads/geological_similarity/schist/*.jpg\")\n",
    "for myFile in files:\n",
    "    image = cv2.imread (myFile)\n",
    "    schist_data.append (image)\n",
    "\n",
    "print('schist_data shape:', np.array(schist_data).shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame(columns=list(range(2352)))\n",
    "for i in range(len(schist_data)):\n",
    "         df1.loc[i]=schist_data[i].flatten()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.DataFrame(columns=list(range(2352)))\n",
    "for i in range(len(rhyolite_data)):\n",
    "         df2.loc[i]=rhyolite_data[i].flatten()\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df3 = pd.DataFrame(columns=list(range(2352)))\n",
    "for i in range(len(quartzite_data)):\n",
    "         df3.loc[i]=quartzite_data[i].flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df4 = pd.DataFrame(columns=list(range(2352)))\n",
    "for i in range(len(marble_data)):\n",
    "         df4.loc[i]=marble_data[i].flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df5 = pd.DataFrame(columns=list(range(2352)))\n",
    "for i in range(len(gneiss_data)):\n",
    "         df5.loc[i]=gneiss_data[i].flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df6 = pd.DataFrame(columns=list(range(2352)))\n",
    "for i in range(len(andesite_data)):\n",
    "         df6.loc[i]=andesite_data[i].flatten()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "schist = []\n",
    "for i in range(5000):\n",
    "    schist.append('Schist')\n",
    "df1['Type'] = schist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "rhyolite = []\n",
    "for i in range(5000):\n",
    "    rhyolite.append('Rhyolite')\n",
    "df2['Type'] = rhyolite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "quartzite = []\n",
    "for i in range(5000):\n",
    "    quartzite.append('Quartzite')\n",
    "df3['Type'] = quartzite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "marble = []\n",
    "for i in range(4998):\n",
    "    marble.append('Marble')\n",
    "df4['Type'] = marble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "gneiss = []\n",
    "for i in range(5000):\n",
    "    gneiss.append('Gneiss')\n",
    "df5['Type'] = gneiss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "andesite = []\n",
    "for i in range(5000):\n",
    "    andesite.append('Andesite')\n",
    "df6['Type'] = andesite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "frames = [df1, df2, df3,df4,df5,df6]\n",
    "\n",
    "df_final = pd.concat(frames)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final = df_final.reset_index(inplace = True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_final.to_csv(r'Geological Image Similarity1.csv',index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df= pd.read_csv('Geological Image Similarity1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>...</th>\n",
       "      <th>2343</th>\n",
       "      <th>2344</th>\n",
       "      <th>2345</th>\n",
       "      <th>2346</th>\n",
       "      <th>2347</th>\n",
       "      <th>2348</th>\n",
       "      <th>2349</th>\n",
       "      <th>2350</th>\n",
       "      <th>2351</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>159</td>\n",
       "      <td>153</td>\n",
       "      <td>146</td>\n",
       "      <td>147</td>\n",
       "      <td>149</td>\n",
       "      <td>137</td>\n",
       "      <td>120</td>\n",
       "      <td>137</td>\n",
       "      <td>116</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>61</td>\n",
       "      <td>65</td>\n",
       "      <td>89</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>103</td>\n",
       "      <td>100</td>\n",
       "      <td>101</td>\n",
       "      <td>105</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>137</td>\n",
       "      <td>129</td>\n",
       "      <td>166</td>\n",
       "      <td>165</td>\n",
       "      <td>161</td>\n",
       "      <td>186</td>\n",
       "      <td>176</td>\n",
       "      <td>180</td>\n",
       "      <td>181</td>\n",
       "      <td>173</td>\n",
       "      <td>...</td>\n",
       "      <td>170</td>\n",
       "      <td>175</td>\n",
       "      <td>166</td>\n",
       "      <td>166</td>\n",
       "      <td>166</td>\n",
       "      <td>166</td>\n",
       "      <td>166</td>\n",
       "      <td>165</td>\n",
       "      <td>167</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>215</td>\n",
       "      <td>216</td>\n",
       "      <td>212</td>\n",
       "      <td>216</td>\n",
       "      <td>215</td>\n",
       "      <td>211</td>\n",
       "      <td>220</td>\n",
       "      <td>212</td>\n",
       "      <td>212</td>\n",
       "      <td>214</td>\n",
       "      <td>...</td>\n",
       "      <td>211</td>\n",
       "      <td>210</td>\n",
       "      <td>206</td>\n",
       "      <td>203</td>\n",
       "      <td>201</td>\n",
       "      <td>200</td>\n",
       "      <td>207</td>\n",
       "      <td>205</td>\n",
       "      <td>205</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>180</td>\n",
       "      <td>181</td>\n",
       "      <td>172</td>\n",
       "      <td>148</td>\n",
       "      <td>150</td>\n",
       "      <td>138</td>\n",
       "      <td>151</td>\n",
       "      <td>159</td>\n",
       "      <td>136</td>\n",
       "      <td>166</td>\n",
       "      <td>...</td>\n",
       "      <td>185</td>\n",
       "      <td>189</td>\n",
       "      <td>177</td>\n",
       "      <td>187</td>\n",
       "      <td>190</td>\n",
       "      <td>175</td>\n",
       "      <td>185</td>\n",
       "      <td>188</td>\n",
       "      <td>173</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>86</td>\n",
       "      <td>102</td>\n",
       "      <td>114</td>\n",
       "      <td>74</td>\n",
       "      <td>90</td>\n",
       "      <td>102</td>\n",
       "      <td>84</td>\n",
       "      <td>100</td>\n",
       "      <td>116</td>\n",
       "      <td>102</td>\n",
       "      <td>...</td>\n",
       "      <td>175</td>\n",
       "      <td>181</td>\n",
       "      <td>162</td>\n",
       "      <td>170</td>\n",
       "      <td>171</td>\n",
       "      <td>161</td>\n",
       "      <td>167</td>\n",
       "      <td>168</td>\n",
       "      <td>159</td>\n",
       "      <td>Schist</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29993</th>\n",
       "      <td>59</td>\n",
       "      <td>70</td>\n",
       "      <td>50</td>\n",
       "      <td>71</td>\n",
       "      <td>82</td>\n",
       "      <td>62</td>\n",
       "      <td>68</td>\n",
       "      <td>77</td>\n",
       "      <td>56</td>\n",
       "      <td>64</td>\n",
       "      <td>...</td>\n",
       "      <td>77</td>\n",
       "      <td>76</td>\n",
       "      <td>56</td>\n",
       "      <td>84</td>\n",
       "      <td>80</td>\n",
       "      <td>61</td>\n",
       "      <td>96</td>\n",
       "      <td>92</td>\n",
       "      <td>73</td>\n",
       "      <td>Andesite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29994</th>\n",
       "      <td>119</td>\n",
       "      <td>116</td>\n",
       "      <td>102</td>\n",
       "      <td>118</td>\n",
       "      <td>115</td>\n",
       "      <td>101</td>\n",
       "      <td>125</td>\n",
       "      <td>121</td>\n",
       "      <td>110</td>\n",
       "      <td>109</td>\n",
       "      <td>...</td>\n",
       "      <td>143</td>\n",
       "      <td>137</td>\n",
       "      <td>118</td>\n",
       "      <td>156</td>\n",
       "      <td>152</td>\n",
       "      <td>128</td>\n",
       "      <td>153</td>\n",
       "      <td>149</td>\n",
       "      <td>124</td>\n",
       "      <td>Andesite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29995</th>\n",
       "      <td>114</td>\n",
       "      <td>122</td>\n",
       "      <td>99</td>\n",
       "      <td>119</td>\n",
       "      <td>127</td>\n",
       "      <td>104</td>\n",
       "      <td>116</td>\n",
       "      <td>125</td>\n",
       "      <td>99</td>\n",
       "      <td>137</td>\n",
       "      <td>...</td>\n",
       "      <td>125</td>\n",
       "      <td>127</td>\n",
       "      <td>107</td>\n",
       "      <td>108</td>\n",
       "      <td>110</td>\n",
       "      <td>91</td>\n",
       "      <td>117</td>\n",
       "      <td>119</td>\n",
       "      <td>100</td>\n",
       "      <td>Andesite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29996</th>\n",
       "      <td>133</td>\n",
       "      <td>132</td>\n",
       "      <td>118</td>\n",
       "      <td>138</td>\n",
       "      <td>137</td>\n",
       "      <td>123</td>\n",
       "      <td>139</td>\n",
       "      <td>136</td>\n",
       "      <td>121</td>\n",
       "      <td>138</td>\n",
       "      <td>...</td>\n",
       "      <td>124</td>\n",
       "      <td>117</td>\n",
       "      <td>100</td>\n",
       "      <td>134</td>\n",
       "      <td>126</td>\n",
       "      <td>109</td>\n",
       "      <td>133</td>\n",
       "      <td>125</td>\n",
       "      <td>108</td>\n",
       "      <td>Andesite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29997</th>\n",
       "      <td>170</td>\n",
       "      <td>148</td>\n",
       "      <td>137</td>\n",
       "      <td>145</td>\n",
       "      <td>125</td>\n",
       "      <td>114</td>\n",
       "      <td>137</td>\n",
       "      <td>116</td>\n",
       "      <td>108</td>\n",
       "      <td>144</td>\n",
       "      <td>...</td>\n",
       "      <td>224</td>\n",
       "      <td>203</td>\n",
       "      <td>195</td>\n",
       "      <td>217</td>\n",
       "      <td>195</td>\n",
       "      <td>184</td>\n",
       "      <td>204</td>\n",
       "      <td>182</td>\n",
       "      <td>171</td>\n",
       "      <td>Andesite</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29998 rows × 2353 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         0    1    2    3    4    5    6    7    8    9  ...  2343  2344  \\\n",
       "0      159  153  146  147  149  137  120  137  116   97  ...    61    65   \n",
       "1      137  129  166  165  161  186  176  180  181  173  ...   170   175   \n",
       "2      215  216  212  216  215  211  220  212  212  214  ...   211   210   \n",
       "3      180  181  172  148  150  138  151  159  136  166  ...   185   189   \n",
       "4       86  102  114   74   90  102   84  100  116  102  ...   175   181   \n",
       "...    ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...   ...   ...   \n",
       "29993   59   70   50   71   82   62   68   77   56   64  ...    77    76   \n",
       "29994  119  116  102  118  115  101  125  121  110  109  ...   143   137   \n",
       "29995  114  122   99  119  127  104  116  125   99  137  ...   125   127   \n",
       "29996  133  132  118  138  137  123  139  136  121  138  ...   124   117   \n",
       "29997  170  148  137  145  125  114  137  116  108  144  ...   224   203   \n",
       "\n",
       "       2345  2346  2347  2348  2349  2350  2351      Type  \n",
       "0        89    91    91   103   100   101   105    Schist  \n",
       "1       166   166   166   166   166   165   167    Schist  \n",
       "2       206   203   201   200   207   205   205    Schist  \n",
       "3       177   187   190   175   185   188   173    Schist  \n",
       "4       162   170   171   161   167   168   159    Schist  \n",
       "...     ...   ...   ...   ...   ...   ...   ...       ...  \n",
       "29993    56    84    80    61    96    92    73  Andesite  \n",
       "29994   118   156   152   128   153   149   124  Andesite  \n",
       "29995   107   108   110    91   117   119   100  Andesite  \n",
       "29996   100   134   126   109   133   125   108  Andesite  \n",
       "29997   195   217   195   184   204   182   171  Andesite  \n",
       "\n",
       "[29998 rows x 2353 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.drop(['index'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.utils import shuffle\n",
    "df = shuffle(df)"
   ]
  },
  {
   "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>index</th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>...</th>\n",
       "      <th>2343</th>\n",
       "      <th>2344</th>\n",
       "      <th>2345</th>\n",
       "      <th>2346</th>\n",
       "      <th>2347</th>\n",
       "      <th>2348</th>\n",
       "      <th>2349</th>\n",
       "      <th>2350</th>\n",
       "      <th>2351</th>\n",
       "      <th>Type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>24328</th>\n",
       "      <td>4330</td>\n",
       "      <td>228</td>\n",
       "      <td>231</td>\n",
       "      <td>229</td>\n",
       "      <td>230</td>\n",
       "      <td>233</td>\n",
       "      <td>231</td>\n",
       "      <td>228</td>\n",
       "      <td>230</td>\n",
       "      <td>230</td>\n",
       "      <td>...</td>\n",
       "      <td>137</td>\n",
       "      <td>126</td>\n",
       "      <td>166</td>\n",
       "      <td>221</td>\n",
       "      <td>217</td>\n",
       "      <td>228</td>\n",
       "      <td>241</td>\n",
       "      <td>242</td>\n",
       "      <td>238</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21207</th>\n",
       "      <td>1209</td>\n",
       "      <td>207</td>\n",
       "      <td>208</td>\n",
       "      <td>198</td>\n",
       "      <td>204</td>\n",
       "      <td>205</td>\n",
       "      <td>195</td>\n",
       "      <td>209</td>\n",
       "      <td>207</td>\n",
       "      <td>199</td>\n",
       "      <td>...</td>\n",
       "      <td>192</td>\n",
       "      <td>192</td>\n",
       "      <td>176</td>\n",
       "      <td>193</td>\n",
       "      <td>192</td>\n",
       "      <td>178</td>\n",
       "      <td>192</td>\n",
       "      <td>191</td>\n",
       "      <td>177</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3561</th>\n",
       "      <td>3561</td>\n",
       "      <td>176</td>\n",
       "      <td>184</td>\n",
       "      <td>153</td>\n",
       "      <td>183</td>\n",
       "      <td>190</td>\n",
       "      <td>163</td>\n",
       "      <td>170</td>\n",
       "      <td>173</td>\n",
       "      <td>157</td>\n",
       "      <td>...</td>\n",
       "      <td>180</td>\n",
       "      <td>181</td>\n",
       "      <td>172</td>\n",
       "      <td>187</td>\n",
       "      <td>188</td>\n",
       "      <td>178</td>\n",
       "      <td>187</td>\n",
       "      <td>188</td>\n",
       "      <td>178</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8364</th>\n",
       "      <td>3364</td>\n",
       "      <td>82</td>\n",
       "      <td>76</td>\n",
       "      <td>71</td>\n",
       "      <td>79</td>\n",
       "      <td>73</td>\n",
       "      <td>68</td>\n",
       "      <td>76</td>\n",
       "      <td>71</td>\n",
       "      <td>68</td>\n",
       "      <td>...</td>\n",
       "      <td>97</td>\n",
       "      <td>95</td>\n",
       "      <td>95</td>\n",
       "      <td>85</td>\n",
       "      <td>81</td>\n",
       "      <td>86</td>\n",
       "      <td>120</td>\n",
       "      <td>119</td>\n",
       "      <td>123</td>\n",
       "      <td>Rhyolite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19256</th>\n",
       "      <td>4256</td>\n",
       "      <td>17</td>\n",
       "      <td>38</td>\n",
       "      <td>69</td>\n",
       "      <td>14</td>\n",
       "      <td>33</td>\n",
       "      <td>66</td>\n",
       "      <td>19</td>\n",
       "      <td>31</td>\n",
       "      <td>73</td>\n",
       "      <td>...</td>\n",
       "      <td>15</td>\n",
       "      <td>35</td>\n",
       "      <td>76</td>\n",
       "      <td>33</td>\n",
       "      <td>52</td>\n",
       "      <td>87</td>\n",
       "      <td>53</td>\n",
       "      <td>72</td>\n",
       "      <td>105</td>\n",
       "      <td>Marble</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28290</th>\n",
       "      <td>3292</td>\n",
       "      <td>118</td>\n",
       "      <td>110</td>\n",
       "      <td>97</td>\n",
       "      <td>83</td>\n",
       "      <td>75</td>\n",
       "      <td>68</td>\n",
       "      <td>64</td>\n",
       "      <td>58</td>\n",
       "      <td>63</td>\n",
       "      <td>...</td>\n",
       "      <td>121</td>\n",
       "      <td>105</td>\n",
       "      <td>98</td>\n",
       "      <td>123</td>\n",
       "      <td>104</td>\n",
       "      <td>97</td>\n",
       "      <td>121</td>\n",
       "      <td>102</td>\n",
       "      <td>94</td>\n",
       "      <td>Andesite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22442</th>\n",
       "      <td>2444</td>\n",
       "      <td>40</td>\n",
       "      <td>48</td>\n",
       "      <td>61</td>\n",
       "      <td>37</td>\n",
       "      <td>46</td>\n",
       "      <td>60</td>\n",
       "      <td>43</td>\n",
       "      <td>53</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>220</td>\n",
       "      <td>221</td>\n",
       "      <td>225</td>\n",
       "      <td>217</td>\n",
       "      <td>219</td>\n",
       "      <td>220</td>\n",
       "      <td>219</td>\n",
       "      <td>221</td>\n",
       "      <td>222</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20525</th>\n",
       "      <td>527</td>\n",
       "      <td>193</td>\n",
       "      <td>185</td>\n",
       "      <td>178</td>\n",
       "      <td>202</td>\n",
       "      <td>195</td>\n",
       "      <td>186</td>\n",
       "      <td>214</td>\n",
       "      <td>207</td>\n",
       "      <td>198</td>\n",
       "      <td>...</td>\n",
       "      <td>223</td>\n",
       "      <td>224</td>\n",
       "      <td>222</td>\n",
       "      <td>224</td>\n",
       "      <td>225</td>\n",
       "      <td>223</td>\n",
       "      <td>224</td>\n",
       "      <td>225</td>\n",
       "      <td>223</td>\n",
       "      <td>Gneiss</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6374</th>\n",
       "      <td>1374</td>\n",
       "      <td>62</td>\n",
       "      <td>70</td>\n",
       "      <td>63</td>\n",
       "      <td>78</td>\n",
       "      <td>86</td>\n",
       "      <td>79</td>\n",
       "      <td>59</td>\n",
       "      <td>69</td>\n",
       "      <td>63</td>\n",
       "      <td>...</td>\n",
       "      <td>73</td>\n",
       "      <td>78</td>\n",
       "      <td>79</td>\n",
       "      <td>43</td>\n",
       "      <td>46</td>\n",
       "      <td>50</td>\n",
       "      <td>63</td>\n",
       "      <td>66</td>\n",
       "      <td>70</td>\n",
       "      <td>Rhyolite</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>2008</td>\n",
       "      <td>100</td>\n",
       "      <td>110</td>\n",
       "      <td>98</td>\n",
       "      <td>97</td>\n",
       "      <td>107</td>\n",
       "      <td>94</td>\n",
       "      <td>103</td>\n",
       "      <td>116</td>\n",
       "      <td>100</td>\n",
       "      <td>...</td>\n",
       "      <td>164</td>\n",
       "      <td>168</td>\n",
       "      <td>157</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>147</td>\n",
       "      <td>136</td>\n",
       "      <td>136</td>\n",
       "      <td>142</td>\n",
       "      <td>Schist</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29998 rows × 2354 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       index    0    1    2    3    4    5    6    7    8  ...  2343  2344  \\\n",
       "24328   4330  228  231  229  230  233  231  228  230  230  ...   137   126   \n",
       "21207   1209  207  208  198  204  205  195  209  207  199  ...   192   192   \n",
       "3561    3561  176  184  153  183  190  163  170  173  157  ...   180   181   \n",
       "8364    3364   82   76   71   79   73   68   76   71   68  ...    97    95   \n",
       "19256   4256   17   38   69   14   33   66   19   31   73  ...    15    35   \n",
       "...      ...  ...  ...  ...  ...  ...  ...  ...  ...  ...  ...   ...   ...   \n",
       "28290   3292  118  110   97   83   75   68   64   58   63  ...   121   105   \n",
       "22442   2444   40   48   61   37   46   60   43   53   70  ...   220   221   \n",
       "20525    527  193  185  178  202  195  186  214  207  198  ...   223   224   \n",
       "6374    1374   62   70   63   78   86   79   59   69   63  ...    73    78   \n",
       "2008    2008  100  110   98   97  107   94  103  116  100  ...   164   168   \n",
       "\n",
       "       2345  2346  2347  2348  2349  2350  2351      Type  \n",
       "24328   166   221   217   228   241   242   238    Gneiss  \n",
       "21207   176   193   192   178   192   191   177    Gneiss  \n",
       "3561    172   187   188   178   187   188   178    Schist  \n",
       "8364     95    85    81    86   120   119   123  Rhyolite  \n",
       "19256    76    33    52    87    53    72   105    Marble  \n",
       "...     ...   ...   ...   ...   ...   ...   ...       ...  \n",
       "28290    98   123   104    97   121   102    94  Andesite  \n",
       "22442   225   217   219   220   219   221   222    Gneiss  \n",
       "20525   222   224   225   223   224   225   223    Gneiss  \n",
       "6374     79    43    46    50    63    66    70  Rhyolite  \n",
       "2008    157   147   147   147   136   136   142    Schist  \n",
       "\n",
       "[29998 rows x 2354 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=df.drop(['Type','index'],axis=1)\n",
    "Y = df['Type']\n",
    "X_train,X_test,Y_train,Y_test = train_test_split(X,Y,test_size = 0.33)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "accuracy_list = []\n",
    "for i in range(95,100):\n",
    "    model = RandomForestClassifier(n_estimators=i)\n",
    "    model.fit(X_train, Y_train)  #fit the model\n",
    "    pred = model.predict(X_test)\n",
    "    accuracy_list.append(accuracy_score(Y_test, pred))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.935959595959596,\n",
       " 0.9366666666666666,\n",
       " 0.9378787878787879,\n",
       " 0.9378787878787879,\n",
       " 0.9372727272727273,\n",
       " 0.937070707070707,\n",
       " 0.938989898989899,\n",
       " 0.9351515151515152,\n",
       " 0.9376767676767677,\n",
       " 0.9384848484848485]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dealing with Deep Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "dl_data=np.concatenate((schist_data, rhyolite_data,quartzite_data,marble_data,gneiss_data,andesite_data), axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "dl_data = np.array(dl_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Labeling Data 1-schist , 2- rhyolite , 3-quartzite , 4-marble , 5-gneiss , 6-andesite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "label_data = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(5000):\n",
    "    label_data.append(1)\n",
    "for i in range(5000):\n",
    "    label_data.append(2)\n",
    "for i in range(5000):\n",
    "    label_data.append(3)\n",
    "for i in range(4998):\n",
    "    label_data.append(4)\n",
    "for i in range(5000):\n",
    "    label_data.append(5)\n",
    "for i in range(5000):\n",
    "    label_data.append(6)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29998"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(label_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random\n",
    "c = list(zip(dl_data, label_data))\n",
    "\n",
    "random.shuffle(c)\n",
    "\n",
    "dl_data, label_data = zip(*c)\n",
    "X_tr,X_te,Y_tr,Y_te = train_test_split(dl_data,label_data , test_size=0.33)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 27.9162 - accuracy: 0.4769\n",
      "Epoch 2/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 8.2967 - accuracy: 0.5716\n",
      "Epoch 3/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 3.5382 - accuracy: 0.5941\n",
      "Epoch 4/10\n",
      "629/629 [==============================] - 2s 4ms/step - loss: 2.0544 - accuracy: 0.6209\n",
      "Epoch 5/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 1.1745 - accuracy: 0.6589\n",
      "Epoch 6/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 0.7608 - accuracy: 0.6810\n",
      "Epoch 7/10\n",
      "629/629 [==============================] - 2s 4ms/step - loss: 0.6954 - accuracy: 0.7049\n",
      "Epoch 8/10\n",
      "629/629 [==============================] - 2s 4ms/step - loss: 0.6568 - accuracy: 0.7142\n",
      "Epoch 9/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 0.6169 - accuracy: 0.7402\n",
      "Epoch 10/10\n",
      "629/629 [==============================] - 3s 4ms/step - loss: 0.6113 - accuracy: 0.7434\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow.python.keras.callbacks.History at 0x1edc027c278>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GeographicalModel = keras.Sequential([\n",
    "                               keras.layers.Flatten(input_shape = (28,28,3)), # as we have seen our data is in 28,28,3\n",
    "                               keras.layers.Dense(128,activation='relu'),\n",
    "                               keras.layers.Dense(10,activation = 'softmax')\n",
    "])\n",
    "GeographicalModel.compile(optimizer = 'adam' , loss = 'sparse_categorical_crossentropy' , metrics = ['accuracy'])\n",
    "GeographicalModel.fit(x=np.array(X_tr), y=np.array(Y_tr),epochs = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = []\n",
    "for i in range(len(X_te)):\n",
    "    img = X_te[i]\n",
    "    img = (np.expand_dims(img,0)) \n",
    "    result = GeographicalModel.predict(img) \n",
    "    correctResult = np.argmax(result)\n",
    "    y_pred.append(correctResult)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 2,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 5,\n",
       " 1,\n",
       " 6,\n",
       " 6,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 1,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 3,\n",
       " 2,\n",
       " 4,\n",
       " 5,\n",
       " 2,\n",
       " 3,\n",
       " 5,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 1,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 6,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 2,\n",
       " 4,\n",
       " 3,\n",
       " 2,\n",
       " 4,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 1,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 2,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 5,\n",
       " 1,\n",
       " 4,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 2,\n",
       " 6,\n",
       " 4,\n",
       " 4,\n",
       " 3,\n",
       " 6,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 1,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 1,\n",
       " 6,\n",
       " 4,\n",
       " 4,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 3,\n",
       " 4,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 1,\n",
       " 2,\n",
       " 4,\n",
       " 4,\n",
       " 1,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 3,\n",
       " 3,\n",
       " 6,\n",
       " 3,\n",
       " 1,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 5,\n",
       " 1,\n",
       " 1,\n",
       " 1,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 5,\n",
       " 2,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 4,\n",
       " 1,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 3,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 1,\n",
       " 5,\n",
       " 3,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 2,\n",
       " 4,\n",
       " 5,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 1,\n",
       " 2,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 1,\n",
       " 3,\n",
       " 4,\n",
       " 1,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 1,\n",
       " 6,\n",
       " 2,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 2,\n",
       " 1,\n",
       " 5,\n",
       " 1,\n",
       " 5,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 6,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 1,\n",
       " 5,\n",
       " 2,\n",
       " 1,\n",
       " 4,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 1,\n",
       " 1,\n",
       " 4,\n",
       " 6,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 6,\n",
       " 3,\n",
       " 3,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 3,\n",
       " 1,\n",
       " 3,\n",
       " 6,\n",
       " 6,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 3,\n",
       " 2,\n",
       " 2,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 4,\n",
       " 2,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 1,\n",
       " 5,\n",
       " 3,\n",
       " 3,\n",
       " 1,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 1,\n",
       " 5,\n",
       " 6,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 2,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 1,\n",
       " 1,\n",
       " 6,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 2,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 1,\n",
       " 5,\n",
       " 1,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 1,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 1,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 1,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 4,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 1,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 5,\n",
       " 1,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 1,\n",
       " 3,\n",
       " 3,\n",
       " 6,\n",
       " 2,\n",
       " 4,\n",
       " 1,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 3,\n",
       " 2,\n",
       " 2,\n",
       " 2,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 2,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 2,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 2,\n",
       " 3,\n",
       " 1,\n",
       " 4,\n",
       " 6,\n",
       " 2,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 1,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 2,\n",
       " 2,\n",
       " 1,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 4,\n",
       " 5,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 2,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 1,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 6,\n",
       " 1,\n",
       " 4,\n",
       " 1,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 2,\n",
       " 2,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 3,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 1,\n",
       " 3,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 1,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " 3,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 1,\n",
       " 3,\n",
       " 4,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 3,\n",
       " 2,\n",
       " 2,\n",
       " 3,\n",
       " 3,\n",
       " 3,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 2,\n",
       " 4,\n",
       " 3,\n",
       " 6,\n",
       " 3,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 1,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 1,\n",
       " 6,\n",
       " 1,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 4,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 3,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 2,\n",
       " 2,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 1,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 4,\n",
       " 2,\n",
       " 6,\n",
       " 2,\n",
       " 4,\n",
       " 1,\n",
       " 1,\n",
       " 2,\n",
       " 2,\n",
       " 1,\n",
       " 3,\n",
       " 1,\n",
       " 3,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 5,\n",
       " 2,\n",
       " 6,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 3,\n",
       " 1,\n",
       " 6,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 1,\n",
       " 2,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 4,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 2,\n",
       " 4,\n",
       " 3,\n",
       " 2,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 4,\n",
       " 3,\n",
       " 4,\n",
       " 4,\n",
       " 1,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 3,\n",
       " 1,\n",
       " 6,\n",
       " 5,\n",
       " 4,\n",
       " 2,\n",
       " 4,\n",
       " 1,\n",
       " 4,\n",
       " 4,\n",
       " 6,\n",
       " 2,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 1,\n",
       " 2,\n",
       " 6,\n",
       " 6,\n",
       " 6,\n",
       " 4,\n",
       " 5,\n",
       " 6,\n",
       " 1,\n",
       " 5,\n",
       " 1,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 1,\n",
       " 2,\n",
       " 3,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 3,\n",
       " 2,\n",
       " 1,\n",
       " 4,\n",
       " 5,\n",
       " 1,\n",
       " 2,\n",
       " 5,\n",
       " 2,\n",
       " 2,\n",
       " 6,\n",
       " 5,\n",
       " 5,\n",
       " 6,\n",
       " 3,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 4,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 5,\n",
       " 6,\n",
       " 5,\n",
       " 4,\n",
       " 6,\n",
       " 5,\n",
       " 6,\n",
       " 6,\n",
       " 2,\n",
       " 3,\n",
       " 2,\n",
       " 3,\n",
       " 6,\n",
       " 1,\n",
       " 3,\n",
       " 5,\n",
       " 3,\n",
       " 6,\n",
       " 5,\n",
       " 2,\n",
       " 3,\n",
       " 4,\n",
       " ...]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7721212121212121"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(Y_te, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}