Definition
Constraint-based mining is the research area studying the development of data mining algorithms that search through a pattern or model space restricted by constraints. The term is usually used to refer to algorithms that search for patterns only. The most well-known instance of constraint-based mining is the mining of frequent patterns. Constraints are needed in pattern mining algorithms to increase the efficiency of the search and to reduce the number of patterns that are presented to the user, thus making knowledge discovery more effective and useful.
Motivation and Background
Constraint-based pattern mining is a generalization of frequent itemset mining. For an introduction to frequent itemset mining, see Frequent Patterns.A constraint-based mining problem is specified by providing the following elements:
A database \(\mathcal{D}\), usually consisting of independent transactions (or instances)
A hypothesis space \(\mathcal{L}\) of patterns
A constraint \(q(\theta...
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Recommended Reading
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Nijssen, S. (2011). Constraint-Based Mining. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_164
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DOI: https://doi.org/10.1007/978-0-387-30164-8_164
Publisher Name: Springer, Boston, MA
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