Stream analytics on the fly: Beyond parameters!

Blog post of the day: Early detection of trends in twitter streams

Generally model driven approaches are employed for analyzing data streams. This is mostly pattern oriented or parametric. Hence it will be looking for specific occurrences for distinct patterns and predefined models. What if a data driven approach can perform well? Stanislav Nikolov writes about this in his blog on computational amusements. In his approach, the weight of each vote depends on the similarity, or distance between the example and the observation according to a decaying exponential. Read more at  Early detection of twitter trends: 


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