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Entry time:
Tue Feb 3 10:54:17 2026
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<p> <table width="98%" align="center" cellspacing="1" style="border:1px solid #486090;"> <tbody> <tr> <td cellpadding="3px" style="background-color:#486090; font-weidht:bold; color:white;">Quote:</td></tr> <tr> <td cellpadding="10px" style="background-color:#FFFFB0;"><p>Also, I should mention, SVM is a great way to not only build functions,<br /> but also visualise higher dimensions in 2D space:<br /> <a href="http://scikit-learn.org/stable/modules/svm.html">http://scikit-learn.org/stable/modules/svm.html</a><br /> (see 1.4.2. Regression)</p> <p> </p> <p>Yes, overfitting is a concern. But that will happen with 2 or 8 or 80 features if you have only a limited qty of triggers (events). Decreasing features does does not decrease overfitting. Only increasing the qty of events improves this condition.<br /> You can use cross-validation to compensate. This shuffles small dataset into larger, safer datasets:<br /> <a href="http://scikit-learn.org/stable/modules/cross_validation.html">http://scikit-learn.org/stable/modules/cross_validation.html</a> Download this app: <a href="http://www.nutonian.com/products/eureqa/">http://www.nutonian.com/products/eureqa/</a></p></td> </tr> </tbody> </table> </p><p> </p>
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