An Inductive Learning Algorithm for Production Rule Discovery
نویسندگان
چکیده
Data mining is the search for relationships and global patterns that exist in large databases. One of the main problems for data mining is that the number of possible relationships is very large, thus prohibiting the search for the correct ones by validating each of them. Hence we need intelligent data mine tools, as taken from the domain of machine learning. In this paper we present a new inductive machine learning algorithm called ILA. The system generates rules in canonical form from a set of examples. We also describe application of ILA to a range of data sets with different number of attributes and classes. The results obtained show that ILA is more general and robust than most other algorithms for inductive learning. Most of the time, the worst case of ILA appears to be comparable to the best case of some well-known algorithms such as AQ and ID3, if not better.
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