Abstract
When the evolution of variables over time is relevant to a classification task, established classifiers cannot be applied directly as the typical input format (data table) is not appropriate. We propose a new representation of temporal patterns that includes constraints on (partial) presence, (partial) absence as well as the duration of temporal predicates. A general-to-specific search-based algorithm is presented to derive classification rules. The approach evaluates promising on artificial and real data.
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Peter, S., Höppner, F. (2010). Finding Temporal Patterns Using Constraints on (Partial) Absence, Presence and Duration. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15387-7_48
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DOI: https://doi.org/10.1007/978-3-642-15387-7_48
Publisher Name: Springer, Berlin, Heidelberg
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