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by esquire_900
1830 days ago
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I would say manual feature extraction? Your custom extraction could reduce the variable lengths to a uniform dimension (same number of features for every input), which can then be used by almost any algorithm. These automatic extractions are very statistical in nature indeed, but for some datasets domain insights are more valuable and give more usable features (in my opinion). I found quite some datasets where manual features + gradient boosted trees give better results then automated statistical methods. Often combinations give better results :) |
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