Thanks for the excellent explanation, and many congratulations on your thesis!:)
Could you point to any resources on time series analysis? While i am well familiar with supervised/unsupervised learning methods for tasks like classification, anomaly detection etc, analyzing time series is a different beast. And most machine learning literature (eosl?) doesn't seem to address time series data either.
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Thanks for the excellent explanation, and many congratulations on your thesis!:)
Could you point to any resources on time series analysis? While i am well familiar with supervised/unsupervised learning methods for tasks like classification, anomaly detection etc, analyzing time series is a different beast. And most machine learning literature (eosl?) doesn't seem to address time series data either.
Thanks! I'm afraid my background, like yours, is more in methods that are not specialized for time series, and so I couldn't credibly give any comprehensive references. My understanding is that a lot of methods designed specifically for time series draw heavily on the theory of stochastic processes. For example http://en.wikipedia.org/wiki/Autoregressive_model, http://en.wikipedia.org/wiki/Autoregressive%E2%80%93moving-a.... I once took a course called Signals, Systems, and Inference that covers some of these ideas (full course notes here http://ocw.mit.edu/courses/electrical-engineering-and-comput...), but that's about as far as I've gotten along that road.