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Old 04-10-2013, 01:55 PM
Moobb Moobb is offline
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Join Date: Apr 2013
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Default Lecture 3 Q&A independence of parameter inputs

There is a discussion about the importance of having independent input data and how this propagates to features. Is it true that features necessarily inherit independence from data? If they don't, how bad is that? For example, in Finance there are quite a few studies using support vector machines using a grid defined by different moving averages, which overlap (1w, 1m, etc). In this case the features are clearly not independent. Would this be seen as a questionable procedure?
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