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6 changed files with 805 additions and 174 deletions
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]
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},
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{
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"ename": "NameError",
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"evalue": "name 'pd' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
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||||
" <td>7.383645</td>\n",
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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|
||||
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|
||||
" <td>0.456576</td>\n",
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||||
" <td>8.318859</td>\n",
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||||
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||||
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||||
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||||
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|
||||
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||||
" <td>0.482429</td>\n",
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||||
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|
||||
" <td>0.484888</td>\n",
|
||||
" <td>0.485017</td>\n",
|
||||
" <td>0.002168</td>\n",
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||||
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||||
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||||
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||||
" <td>14.902358</td>\n",
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" <td>0.737693</td>\n",
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||||
" <td>5.975091</td>\n",
|
||||
" <td>0.171150</td>\n",
|
||||
" <td>0.5</td>\n",
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||||
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|
||||
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" <td>100</td>\n",
|
||||
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" <td>0.469598</td>\n",
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" <td>0.474490</td>\n",
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" <td>0.473637</td>\n",
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" <td>0.472575</td>\n",
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" <td>0.002134</td>\n",
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" <td>10</td>\n",
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" <th>9</th>\n",
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" <td>12.677349</td>\n",
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" <td>0.145143</td>\n",
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" <td>4.374204</td>\n",
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" <td>0.175674</td>\n",
|
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" <td>0.5</td>\n",
|
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" <td>False</td>\n",
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" <td>0.1</td>\n",
|
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" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 0.5, 'classifier__fit_pr...</td>\n",
|
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" <td>0.468872</td>\n",
|
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" <td>0.476451</td>\n",
|
||||
" <td>0.470921</td>\n",
|
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" <td>0.472082</td>\n",
|
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" <td>0.003201</td>\n",
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" <td>11</td>\n",
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" <th>5</th>\n",
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" <td>13.423686</td>\n",
|
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" <td>0.482872</td>\n",
|
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" <td>8.008324</td>\n",
|
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" <td>0.442975</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.1</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" <td>{'classifier__alpha': 0.5, 'classifier__fit_pr...</td>\n",
|
||||
" <td>0.465726</td>\n",
|
||||
" <td>0.474548</td>\n",
|
||||
" <td>0.471879</td>\n",
|
||||
" <td>0.470718</td>\n",
|
||||
" <td>0.003694</td>\n",
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" <td>12</td>\n",
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||||
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" <th>1</th>\n",
|
||||
" <td>13.819117</td>\n",
|
||||
" <td>0.838347</td>\n",
|
||||
" <td>6.161175</td>\n",
|
||||
" <td>0.336590</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.05</td>\n",
|
||||
" <td>20</td>\n",
|
||||
" <td>{'classifier__alpha': 0.5, 'classifier__fit_pr...</td>\n",
|
||||
" <td>0.463395</td>\n",
|
||||
" <td>0.473982</td>\n",
|
||||
" <td>0.471262</td>\n",
|
||||
" <td>0.469546</td>\n",
|
||||
" <td>0.004489</td>\n",
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" <td>13</td>\n",
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" <th>4</th>\n",
|
||||
" <td>13.281476</td>\n",
|
||||
" <td>0.588822</td>\n",
|
||||
" <td>8.335852</td>\n",
|
||||
" <td>0.254627</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>True</td>\n",
|
||||
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|
||||
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|
||||
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|
||||
" <td>0.458734</td>\n",
|
||||
" <td>0.468053</td>\n",
|
||||
" <td>0.464418</td>\n",
|
||||
" <td>0.463735</td>\n",
|
||||
" <td>0.003835</td>\n",
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||||
" <td>7.282247</td>\n",
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||||
" <td>0.444940</td>\n",
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||||
" <td>3.567094</td>\n",
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||||
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||||
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||||
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||||
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||||
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|
||||
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||||
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|
||||
" <td>0.450160</td>\n",
|
||||
" <td>0.446180</td>\n",
|
||||
" <td>0.444843</td>\n",
|
||||
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||||
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" <th>17</th>\n",
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||||
" <td>7.098797</td>\n",
|
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" <td>0.196241</td>\n",
|
||||
" <td>3.838628</td>\n",
|
||||
" <td>0.091128</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.1</td>\n",
|
||||
" <td>100</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
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||||
" <td>0.436488</td>\n",
|
||||
" <td>0.444503</td>\n",
|
||||
" <td>0.445900</td>\n",
|
||||
" <td>0.442297</td>\n",
|
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" <td>0.004147</td>\n",
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" <td>16</td>\n",
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||||
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||||
" <tr>\n",
|
||||
" <th>18</th>\n",
|
||||
" <td>7.492791</td>\n",
|
||||
" <td>0.288889</td>\n",
|
||||
" <td>3.843224</td>\n",
|
||||
" <td>0.073438</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>False</td>\n",
|
||||
" <td>0.05</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
|
||||
" <td>0.428196</td>\n",
|
||||
" <td>0.431945</td>\n",
|
||||
" <td>0.430160</td>\n",
|
||||
" <td>0.430100</td>\n",
|
||||
" <td>0.001531</td>\n",
|
||||
" <td>17</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>21</th>\n",
|
||||
" <td>7.229826</td>\n",
|
||||
" <td>0.099823</td>\n",
|
||||
" <td>3.656332</td>\n",
|
||||
" <td>0.073780</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>False</td>\n",
|
||||
" <td>0.1</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
|
||||
" <td>0.403130</td>\n",
|
||||
" <td>0.410170</td>\n",
|
||||
" <td>0.409801</td>\n",
|
||||
" <td>0.407700</td>\n",
|
||||
" <td>0.003235</td>\n",
|
||||
" <td>18</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>13</th>\n",
|
||||
" <td>7.158370</td>\n",
|
||||
" <td>0.169818</td>\n",
|
||||
" <td>3.765632</td>\n",
|
||||
" <td>0.082924</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.05</td>\n",
|
||||
" <td>20</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
|
||||
" <td>0.399237</td>\n",
|
||||
" <td>0.412872</td>\n",
|
||||
" <td>0.407982</td>\n",
|
||||
" <td>0.406697</td>\n",
|
||||
" <td>0.005640</td>\n",
|
||||
" <td>19</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>16</th>\n",
|
||||
" <td>7.064643</td>\n",
|
||||
" <td>0.119529</td>\n",
|
||||
" <td>3.810983</td>\n",
|
||||
" <td>0.125897</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.1</td>\n",
|
||||
" <td>20</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
|
||||
" <td>0.388060</td>\n",
|
||||
" <td>0.399247</td>\n",
|
||||
" <td>0.396325</td>\n",
|
||||
" <td>0.394544</td>\n",
|
||||
" <td>0.004737</td>\n",
|
||||
" <td>20</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>0</th>\n",
|
||||
" <td>13.749660</td>\n",
|
||||
" <td>0.465174</td>\n",
|
||||
" <td>6.407841</td>\n",
|
||||
" <td>0.549166</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.05</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 0.5, 'classifier__fit_pr...</td>\n",
|
||||
" <td>0.384852</td>\n",
|
||||
" <td>0.386487</td>\n",
|
||||
" <td>0.386796</td>\n",
|
||||
" <td>0.386045</td>\n",
|
||||
" <td>0.000853</td>\n",
|
||||
" <td>21</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>3</th>\n",
|
||||
" <td>15.954147</td>\n",
|
||||
" <td>0.318013</td>\n",
|
||||
" <td>6.337361</td>\n",
|
||||
" <td>0.261697</td>\n",
|
||||
" <td>0.5</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.1</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 0.5, 'classifier__fit_pr...</td>\n",
|
||||
" <td>0.369785</td>\n",
|
||||
" <td>0.375645</td>\n",
|
||||
" <td>0.375858</td>\n",
|
||||
" <td>0.373763</td>\n",
|
||||
" <td>0.002814</td>\n",
|
||||
" <td>22</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>12</th>\n",
|
||||
" <td>7.120198</td>\n",
|
||||
" <td>0.050452</td>\n",
|
||||
" <td>3.833905</td>\n",
|
||||
" <td>0.069540</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.05</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
|
||||
" <td>0.277741</td>\n",
|
||||
" <td>0.280564</td>\n",
|
||||
" <td>0.285337</td>\n",
|
||||
" <td>0.281214</td>\n",
|
||||
" <td>0.003135</td>\n",
|
||||
" <td>23</td>\n",
|
||||
" </tr>\n",
|
||||
" <tr>\n",
|
||||
" <th>15</th>\n",
|
||||
" <td>7.497707</td>\n",
|
||||
" <td>0.183054</td>\n",
|
||||
" <td>3.870714</td>\n",
|
||||
" <td>0.062888</td>\n",
|
||||
" <td>1</td>\n",
|
||||
" <td>True</td>\n",
|
||||
" <td>0.1</td>\n",
|
||||
" <td>5</td>\n",
|
||||
" <td>{'classifier__alpha': 1, 'classifier__fit_prio...</td>\n",
|
||||
" <td>0.255578</td>\n",
|
||||
" <td>0.263381</td>\n",
|
||||
" <td>0.266184</td>\n",
|
||||
" <td>0.261714</td>\n",
|
||||
" <td>0.004487</td>\n",
|
||||
" <td>24</td>\n",
|
||||
" </tr>\n",
|
||||
" </tbody>\n",
|
||||
"</table>\n",
|
||||
"</div>"
|
||||
],
|
||||
"text/plain": [
|
||||
" mean_fit_time std_fit_time mean_score_time std_score_time \\\n",
|
||||
"7 14.549476 0.361685 8.476837 0.222398 \n",
|
||||
"10 11.235289 0.130426 4.092868 0.082518 \n",
|
||||
"19 7.383645 0.138110 4.130709 0.250048 \n",
|
||||
"11 10.435154 0.305144 3.882101 0.128886 \n",
|
||||
"8 13.643193 0.310696 4.173707 0.142980 \n",
|
||||
"22 7.048340 0.050070 3.172948 0.152418 \n",
|
||||
"23 7.564685 0.146092 2.374111 0.285026 \n",
|
||||
"20 7.172353 0.212599 3.747219 0.130217 \n",
|
||||
"6 14.276345 0.456576 8.318859 0.268701 \n",
|
||||
"2 14.902358 0.737693 5.975091 0.171150 \n",
|
||||
"9 12.677349 0.145143 4.374204 0.175674 \n",
|
||||
"5 13.423686 0.482872 8.008324 0.442975 \n",
|
||||
"1 13.819117 0.838347 6.161175 0.336590 \n",
|
||||
"4 13.281476 0.588822 8.335852 0.254627 \n",
|
||||
"14 7.282247 0.444940 3.567094 0.044519 \n",
|
||||
"17 7.098797 0.196241 3.838628 0.091128 \n",
|
||||
"18 7.492791 0.288889 3.843224 0.073438 \n",
|
||||
"21 7.229826 0.099823 3.656332 0.073780 \n",
|
||||
"13 7.158370 0.169818 3.765632 0.082924 \n",
|
||||
"16 7.064643 0.119529 3.810983 0.125897 \n",
|
||||
"0 13.749660 0.465174 6.407841 0.549166 \n",
|
||||
"3 15.954147 0.318013 6.337361 0.261697 \n",
|
||||
"12 7.120198 0.050452 3.833905 0.069540 \n",
|
||||
"15 7.497707 0.183054 3.870714 0.062888 \n",
|
||||
"\n",
|
||||
" param_classifier__alpha param_classifier__fit_prior \\\n",
|
||||
"7 0.5 False \n",
|
||||
"10 0.5 False \n",
|
||||
"19 1 False \n",
|
||||
"11 0.5 False \n",
|
||||
"8 0.5 False \n",
|
||||
"22 1 False \n",
|
||||
"23 1 False \n",
|
||||
"20 1 False \n",
|
||||
"6 0.5 False \n",
|
||||
"2 0.5 True \n",
|
||||
"9 0.5 False \n",
|
||||
"5 0.5 True \n",
|
||||
"1 0.5 True \n",
|
||||
"4 0.5 True \n",
|
||||
"14 1 True \n",
|
||||
"17 1 True \n",
|
||||
"18 1 False \n",
|
||||
"21 1 False \n",
|
||||
"13 1 True \n",
|
||||
"16 1 True \n",
|
||||
"0 0.5 True \n",
|
||||
"3 0.5 True \n",
|
||||
"12 1 True \n",
|
||||
"15 1 True \n",
|
||||
"\n",
|
||||
" param_vectorizer__max_df param_vectorizer__min_df \\\n",
|
||||
"7 0.05 20 \n",
|
||||
"10 0.1 20 \n",
|
||||
"19 0.05 20 \n",
|
||||
"11 0.1 100 \n",
|
||||
"8 0.05 100 \n",
|
||||
"22 0.1 20 \n",
|
||||
"23 0.1 100 \n",
|
||||
"20 0.05 100 \n",
|
||||
"6 0.05 5 \n",
|
||||
"2 0.05 100 \n",
|
||||
"9 0.1 5 \n",
|
||||
"5 0.1 100 \n",
|
||||
"1 0.05 20 \n",
|
||||
"4 0.1 20 \n",
|
||||
"14 0.05 100 \n",
|
||||
"17 0.1 100 \n",
|
||||
"18 0.05 5 \n",
|
||||
"21 0.1 5 \n",
|
||||
"13 0.05 20 \n",
|
||||
"16 0.1 20 \n",
|
||||
"0 0.05 5 \n",
|
||||
"3 0.1 5 \n",
|
||||
"12 0.05 5 \n",
|
||||
"15 0.1 5 \n",
|
||||
"\n",
|
||||
" params split0_test_score \\\n",
|
||||
"7 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.518061 \n",
|
||||
"10 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.513897 \n",
|
||||
"19 {'classifier__alpha': 1, 'classifier__fit_prio... 0.496825 \n",
|
||||
"11 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.493247 \n",
|
||||
"8 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.489609 \n",
|
||||
"22 {'classifier__alpha': 1, 'classifier__fit_prio... 0.487456 \n",
|
||||
"23 {'classifier__alpha': 1, 'classifier__fit_prio... 0.485160 \n",
|
||||
"20 {'classifier__alpha': 1, 'classifier__fit_prio... 0.481303 \n",
|
||||
"6 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.482429 \n",
|
||||
"2 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.469598 \n",
|
||||
"9 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.468872 \n",
|
||||
"5 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.465726 \n",
|
||||
"1 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.463395 \n",
|
||||
"4 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.458734 \n",
|
||||
"14 {'classifier__alpha': 1, 'classifier__fit_prio... 0.438189 \n",
|
||||
"17 {'classifier__alpha': 1, 'classifier__fit_prio... 0.436488 \n",
|
||||
"18 {'classifier__alpha': 1, 'classifier__fit_prio... 0.428196 \n",
|
||||
"21 {'classifier__alpha': 1, 'classifier__fit_prio... 0.403130 \n",
|
||||
"13 {'classifier__alpha': 1, 'classifier__fit_prio... 0.399237 \n",
|
||||
"16 {'classifier__alpha': 1, 'classifier__fit_prio... 0.388060 \n",
|
||||
"0 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.384852 \n",
|
||||
"3 {'classifier__alpha': 0.5, 'classifier__fit_pr... 0.369785 \n",
|
||||
"12 {'classifier__alpha': 1, 'classifier__fit_prio... 0.277741 \n",
|
||||
"15 {'classifier__alpha': 1, 'classifier__fit_prio... 0.255578 \n",
|
||||
"\n",
|
||||
" split1_test_score split2_test_score mean_test_score std_test_score \\\n",
|
||||
"7 0.514842 0.511599 0.514834 0.002638 \n",
|
||||
"10 0.515661 0.507867 0.512475 0.003337 \n",
|
||||
"19 0.501045 0.496854 0.498241 0.001983 \n",
|
||||
"11 0.497814 0.502245 0.497769 0.003674 \n",
|
||||
"8 0.495207 0.498154 0.494323 0.003544 \n",
|
||||
"22 0.493865 0.491157 0.490826 0.002627 \n",
|
||||
"23 0.494039 0.490127 0.489776 0.003633 \n",
|
||||
"20 0.490002 0.488269 0.486524 0.003759 \n",
|
||||
"6 0.487735 0.484888 0.485017 0.002168 \n",
|
||||
"2 0.474490 0.473637 0.472575 0.002134 \n",
|
||||
"9 0.476451 0.470921 0.472082 0.003201 \n",
|
||||
"5 0.474548 0.471879 0.470718 0.003694 \n",
|
||||
"1 0.473982 0.471262 0.469546 0.004489 \n",
|
||||
"4 0.468053 0.464418 0.463735 0.003835 \n",
|
||||
"14 0.450160 0.446180 0.444843 0.004978 \n",
|
||||
"17 0.444503 0.445900 0.442297 0.004147 \n",
|
||||
"18 0.431945 0.430160 0.430100 0.001531 \n",
|
||||
"21 0.410170 0.409801 0.407700 0.003235 \n",
|
||||
"13 0.412872 0.407982 0.406697 0.005640 \n",
|
||||
"16 0.399247 0.396325 0.394544 0.004737 \n",
|
||||
"0 0.386487 0.386796 0.386045 0.000853 \n",
|
||||
"3 0.375645 0.375858 0.373763 0.002814 \n",
|
||||
"12 0.280564 0.285337 0.281214 0.003135 \n",
|
||||
"15 0.263381 0.266184 0.261714 0.004487 \n",
|
||||
"\n",
|
||||
" rank_test_score \n",
|
||||
"7 1 \n",
|
||||
"10 2 \n",
|
||||
"19 3 \n",
|
||||
"11 4 \n",
|
||||
"8 5 \n",
|
||||
"22 6 \n",
|
||||
"23 7 \n",
|
||||
"20 8 \n",
|
||||
"6 9 \n",
|
||||
"2 10 \n",
|
||||
"9 11 \n",
|
||||
"5 12 \n",
|
||||
"1 13 \n",
|
||||
"4 14 \n",
|
||||
"14 15 \n",
|
||||
"17 16 \n",
|
||||
"18 17 \n",
|
||||
"21 18 \n",
|
||||
"13 19 \n",
|
||||
"16 20 \n",
|
||||
"0 21 \n",
|
||||
"3 22 \n",
|
||||
"12 23 \n",
|
||||
"15 24 "
|
||||
]
|
||||
},
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from sklearn.model_selection import GridSearchCV\n",
|
||||
"import pandas as pd\n",
|
||||
"\n",
|
||||
"optimisation_pipeline = GridSearchCV(\n",
|
||||
" create_pipeline(),\n",
|
||||
|
|
@ -157,7 +784,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -199,7 +826,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
|
|
@ -207,15 +834,15 @@
|
|||
"output_type": "stream",
|
||||
"text": [
|
||||
"\u001b[38;5;39mFetching cached versions of small-domain-prediction\u001b[0m\n",
|
||||
"\u001b[38;5;39mCopying file for small-domain-prediction-1\u001b[0m\n",
|
||||
"\u001b[38;5;39mCompressing small-domain-prediction-1\u001b[0m\n",
|
||||
"\u001b[38;5;39mModel small-domain-prediction uploaded with version 1\u001b[0m\n"
|
||||
"\u001b[38;5;39mCopying file for small-domain-prediction-2\u001b[0m\n",
|
||||
"\u001b[38;5;39mCompressing small-domain-prediction-2\u001b[0m\n",
|
||||
"\u001b[38;5;39mModel small-domain-prediction uploaded with version 2\u001b[0m\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"'small-domain-prediction:1'"
|
||||
"'small-domain-prediction:2'"
|
||||
]
|
||||
},
|
||||
"execution_count": 6,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue