Learning sequential classifiers from long and noisy discrete-event sequences efficiently
Data Mining and Knowledge Discovery, Volume 29, Issue 6, 2014.
Sequential classifiersEfficient learningLong range sequencesPartial matchingApproximately contiguous sequences
A variety of applications, such as information extraction, intrusion detection and protein fold recognition, can be expressed as sequences of discrete events or elements (rather than unordered sets of features), that is, there is an order dependence among the elements composing each data instance. These applications may be modeled as clas...More
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