Learning sequential classifiers from long and noisy discrete-event sequences efficiently

    Data Mining and Knowledge Discovery, Volume 29, Issue 6, 2014.

    Cited by: 11|Bibtex|Views30|Links
    EI
    Keywords:
    Sequential classifiersEfficient learningLong range sequencesPartial matchingApproximately contiguous sequences

    Abstract:

    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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