I used to be wanting to know if I could Establish/prepare another design (say SVM with RBF kernel) using the characteristics from SVM-RFE (whereby the kernel used is usually a linear kernel).
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Essentially I need to supply aspect reduction output to Naive Bays. I f you could potentially give sample code will likely be better.
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Ahead of undertaking PCA or attribute variety? In my situation it's taking the feature Together with the max benefit as vital attribute.
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– Then I've in comparison the r2 and I have preferred the better design, so I have used its functions picked so that you can do Some others matters.
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Did you accidently involve The category output variable in the info when carrying out the PCA? It should be excluded.
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Is there a method just like a rule of thumb or an algorithm to quickly make your mind up the “finest of the greatest� Say, I exploit n-grams; if I exploit trigrams on the 1000 instance info set, the quantity of features explodes. How can I established SelectKBest to an “x†amount quickly based on the very best? Thanks.
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Considering that most Web sites that I have noticed so far just use the default parameter configuration all through this stage. I recognize that including a grid look for has the next consequenses: