On the Detection of Concept Changes in

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Presentation transcript:

On the Detection of Concept Changes in Time-Varying Data Stream by Testing Exchangeability Shen-Shyang Ho and Harry Wechsler {sho, wechsler}@cs.gmu.edu Department of Computer Science George Mason University Problem: In a data streaming setting, data points are observed one by one. The concepts to be learned from the data stream may change infinitely often. How do we detect the changes efficiently?

A martingale framework was proposed and two tests are suggested [Ho, ICML 2005] Show that the test (MT1) based on Doob's Inequality is an approximation to the sequential probability ratio test (SPRT). Relationship between the threshold value with respect to the size and power of the test is established Mean delay time before a change being detected is estimated. Test (MT2) based on the Hoeffding-Azuma Inequality. Under some assumptions, MT2 has a lower false positive (i.e. Declaring a change when in fact there is no change) rate than MT1.