last update, perhaps
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@@ -797,9 +797,9 @@ predicting the target features of query instances is as follows:</p>
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</div>
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<div class="cell_output docutils container">
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>2nd degree coefficients:
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zero power: -0.22158725223474995
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first power: 0.24121476598003452
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second power: -0.0009532583857747255
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zero power: 4.58641507967355
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first power: -0.2107546970521115
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second power: 0.0003919793592273513
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</pre></div>
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</div>
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<img alt="_images/chapter6_1_1.png" src="_images/chapter6_1_1.png" />
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@@ -1662,11 +1662,13 @@ attributes at each step while growing the tree.</p>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>(426, 30)
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(143, 30)
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Test set accuracy with Logistic Regression: 0.94
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</pre></div>
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</div>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Test set accuracy with Logistic Regression: 0.94
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Test set accuracy with SVM: 0.63
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Test set accuracy with Decision Trees: 0.90
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Test set accuracy with SVM: 0.63
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</pre></div>
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</div>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Test set accuracy with Decision Trees: 0.90
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Test set accuracy Logistic Regression with scaled data: 0.96
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Test set accuracy SVM with scaled data: 0.96
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Test set accuracy with Decision Trees and scaled data: 0.89
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