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-   -   Dependent Data (http://book.caltech.edu/bookforum/showthread.php?t=878)

data_user 07-17-2012 05:38 PM

Dependent Data
 
The independence of data seems to be curtail for both theoretical analysis and practical efficiency. What if the sample (x1,y1)...(xN,yN) consists of correlated points? For example, x1....xN is a realization of a Markov chain. Can we still learn from these data? Do we need to change the standard learning algorithms to account for the dependence? Is it possible to introduce a notion of "effective" number of data points N'<N and then work with the sample if it were independent of size N'?

magdon 07-18-2012 09:37 AM

Re: Dependent Data
 
Unfortunately, there is no easy way to deal with dependent data even if they are generated by a Markov chain.

Quote:

Originally Posted by data_user (Post 3487)
The independence of data seems to be curtail for both theoretical analysis and practical efficiency. What if the sample (x1,y1)...(xN,yN) consists of correlated points? For example, x1....xN is a realization of a Markov chain. Can we still learn from these data? Do we need to change the standard learning algorithms to account for the dependence? Is it possible to introduce a notion of "effective" number of data points N'<N and then work with the sample if it were independent of size N'?


data_user 07-23-2012 07:22 PM

Re: Dependent Data
 
This is a good source of references on the subject:
http://cscs.umich.edu/~crshalizi/not...-learning.html


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