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Old 04-10-2013, 03:08 PM
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yaser yaser is offline
Join Date: Aug 2009
Location: Pasadena, California, USA
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Default Re: Lecture 3 Q&A independence of parameter inputs

Originally Posted by Moobb View Post
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?
Could you use the [lecture3] macro (see the "Including a lecture video segment" thread at the top) to pinpoint the part you are referring to? Thank you.
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