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@JesperDramsch
JesperDramsch committed Feb 11, 2024
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23 changes: 20 additions & 3 deletions _sources/notebooks/5-interpretability.ipynb
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Expand Up @@ -547,7 +547,15 @@
{
"cell_type": "markdown",
"metadata": {},
"source": []
"source": [
"We can see that the permutation importance gives a lower weight to `Culmen Depth` in the Random Forest and a slightly higher importance to `Sex`.\n",
"\n",
"Overall it's similar in that `Culmen Length` is still the most important and `Flipper length` is the second most important, while the relative importance changes somewhat. \n",
"\n",
"These differences can be much more pronounced in more complex models.\n",
"\n",
"The really neat feature is however, that we can apply this to the SVM model, which does not have internal importances!"
]
},
{
"cell_type": "code",
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"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here we can see that `Culmen length` is still the most important and `Sex` is mostly unimportant, but the relative importances of `Culmen depth` and `Flipper length` change."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"fi_rf_test = pd.Series(permutation_importance(rf, X_test, y_test, n_repeats=10, random_state=42), index=features)\n",
"fi_svm_test = pd.Series(permutation_importance(model, X_test, y_test, n_repeats=10, random_state=42), index=features)\n",
"result = permutation_importance(rf, X_test, y_test, n_repeats=10, random_state=42)\n",
"fi_rf_test = pd.Series(result, index=features)\n",
"result = permutation_importance(model, X_test, y_test, n_repeats=10, random_state=42)\n",
"fi_svm_test = pd.Series(result, index=features)\n",
"\n",
"pd.DataFrame({\"RF Train\": fi_rf_train, \"SVM Train\": fi_svm_train, \"RF Test\": fi_rf_test, \"SVM Test\": fi_svm_test}).plot.bar()"
]
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118 changes: 59 additions & 59 deletions notebooks/0-basic-data-prep-and-model.html
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Expand Up @@ -984,38 +984,38 @@ <h2>Machine Learning<a class="headerlink" href="#machine-learning" title="Permal
</thead>
<tbody>
<tr>
<th>34</th>
<td>36.4</td>
<td>17.0</td>
<td>195.0</td>
<th>230</th>
<td>45.2</td>
<td>13.8</td>
<td>215.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>243</th>
<td>52.2</td>
<td>17.1</td>
<td>228.0</td>
<td>MALE</td>
<th>276</th>
<td>46.5</td>
<td>17.9</td>
<td>192.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>312</th>
<td>47.6</td>
<td>18.3</td>
<td>195.0</td>
<th>15</th>
<td>36.6</td>
<td>17.8</td>
<td>185.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>285</th>
<td>51.3</td>
<td>19.9</td>
<td>198.0</td>
<td>MALE</td>
<th>66</th>
<td>35.5</td>
<td>16.2</td>
<td>195.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>46</th>
<td>41.1</td>
<td>19.0</td>
<td>182.0</td>
<th>61</th>
<td>41.3</td>
<td>21.1</td>
<td>195.0</td>
<td>MALE</td>
</tr>
<tr>
Expand All @@ -1026,38 +1026,38 @@ <h2>Machine Learning<a class="headerlink" href="#machine-learning" title="Permal
<td>...</td>
</tr>
<tr>
<th>44</th>
<td>37.0</td>
<td>16.9</td>
<td>185.0</td>
<th>157</th>
<td>46.5</td>
<td>13.5</td>
<td>210.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>236</th>
<td>44.9</td>
<td>13.8</td>
<th>234</th>
<td>47.4</td>
<td>14.6</td>
<td>212.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>83</th>
<td>35.1</td>
<td>19.4</td>
<td>193.0</td>
<td>MALE</td>
<th>32</th>
<td>39.5</td>
<td>17.8</td>
<td>188.0</td>
<td>FEMALE</td>
</tr>
<tr>
<th>31</th>
<td>37.2</td>
<td>18.1</td>
<td>178.0</td>
<th>35</th>
<td>39.2</td>
<td>21.1</td>
<td>196.0</td>
<td>MALE</td>
</tr>
<tr>
<th>121</th>
<td>37.7</td>
<td>19.8</td>
<td>198.0</td>
<th>153</th>
<td>50.0</td>
<td>16.3</td>
<td>230.0</td>
<td>MALE</td>
</tr>
</tbody>
Expand Down Expand Up @@ -1095,48 +1095,48 @@ <h2>Machine Learning<a class="headerlink" href="#machine-learning" title="Permal
</thead>
<tbody>
<tr>
<th>34</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
</tr>
<tr>
<th>243</th>
<th>230</th>
<td>Gentoo penguin (Pygoscelis papua)</td>
</tr>
<tr>
<th>312</th>
<th>276</th>
<td>Chinstrap penguin (Pygoscelis antarctica)</td>
</tr>
<tr>
<th>285</th>
<td>Chinstrap penguin (Pygoscelis antarctica)</td>
<th>15</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
</tr>
<tr>
<th>66</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
</tr>
<tr>
<th>46</th>
<th>61</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
</tr>
<tr>
<th>...</th>
<td>...</td>
</tr>
<tr>
<th>44</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
<th>157</th>
<td>Gentoo penguin (Pygoscelis papua)</td>
</tr>
<tr>
<th>236</th>
<th>234</th>
<td>Gentoo penguin (Pygoscelis papua)</td>
</tr>
<tr>
<th>83</th>
<th>32</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
</tr>
<tr>
<th>31</th>
<th>35</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
</tr>
<tr>
<th>121</th>
<td>Adelie Penguin (Pygoscelis adeliae)</td>
<th>153</th>
<td>Gentoo penguin (Pygoscelis papua)</td>
</tr>
</tbody>
</table>
Expand Down Expand Up @@ -1264,7 +1264,7 @@ <h3>Model Training<a class="headerlink" href="#model-training" title="Permalink
</div>
</div>
<div class="cell_output docutils container">
<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.9871244635193133
<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>0.9914163090128756
</pre></div>
</div>
</div>
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4 changes: 2 additions & 2 deletions notebooks/1-model-evaluation.html
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Expand Up @@ -1146,8 +1146,8 @@ <h2><span class="section-number">1.3.5. </span>Choosing the appropriate Evaluati
</div>
</div>
<div class="cell_output docutils container">
<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{&#39;fit_time&#39;: array([0.00599885, 0.00516748, 0.00515461, 0.00513673, 0.00516844]),
&#39;score_time&#39;: array([0.00435352, 0.00395489, 0.00400567, 0.00393963, 0.00396037]),
<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>{&#39;fit_time&#39;: array([0.00631857, 0.00540304, 0.0053215 , 0.00532579, 0.00522256]),
&#39;score_time&#39;: array([0.00442171, 0.00407219, 0.00416684, 0.0040834 , 0.00409722]),
&#39;test_MCC&#39;: array([0.37796447, 0.27863911, 0.40824829, 0.02424643, 0.08625819]),
&#39;test_ACC&#39;: array([0.73333333, 0.7 , 0.76666667, 0.66666667, 0.62068966])}
</pre></div>
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35 changes: 21 additions & 14 deletions notebooks/5-interpretability.html
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2 changes: 1 addition & 1 deletion searchindex.js
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