small adjustment
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@@ -1509,6 +1509,7 @@ sol <span style="color: #666666">=</span> solvers<span style="color: #666666">.<
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<span style="color: #408080; font-style: italic"># Extract optimal value and solution</span>
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sol[<span style="color: #BA2121">'x'</span>]
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sol[<span style="color: #BA2121">'primal objective'</span>]
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<span style="color: #008000">print</span>(sol[<span style="color: #BA2121">'x'</span>] )
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</pre>
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</div>
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</div>
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@@ -1543,7 +1544,7 @@ $$
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With the slack constants this leads to the additional constraint \( 0\leq \lambda_i \leq C \).
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</p>
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<p>Using the <b>CVXOPT</b> library, the matrix \( P \) would then be defined by the </p>
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<p>Using the <b>CVXOPT</b> library, the matrix \( P \) would then be defined by the above matrix while the KKT conditions would all be collected by the matrix \( G \).</p>
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<!-- !split --><br><br><br><br><br><br><br><br><br><br>
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<h2 id="basic-ideas-of-the-principal-component-analysis-pca">Basic ideas of the Principal Component Analysis (PCA) </h2>
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