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Rule-based Methods

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Encyclopedia of Systems Biology


Rule-based methods are a popular class of techniques in machine learning and data mining (Fürnkranz et al. 2012). They share the goal of finding regularities in data that can be expressed in the form of an IF-THEN rule. Depending on the type of rule that should be found, we can discriminate between association rule discovery and predictive rule learning. In the latter case, one is often also interested in learning a collection of rules that collectively cover the instance space in the sense that they can make a prediction for every possible instance.


Association Rule Discovery

The discovery of association rules typically happens in two phases, which were pioneered in the Apriori algorithm. First, all frequent itemsets (i.e., conditions that cover a certain minimum number of examples) are found. In a second pass, these are then converted into association rules.

For finding all frequent itemsets, Apriorigenerates all rules with a certain minimum frequency in...

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Correspondence to Johannes Fürnkranz .

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Fürnkranz, J. (2013). Rule-based Methods. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY.

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