Presents an inductive machine learning algorithm called CLIP3 (Cover learning using integer programming). CLIP3 is an extension of the CLILP2 algorithm. CLIP3 generates multiple rules for a given concept from two sets of discrete attribute data. It combines the best concepts of tree‐based and rule‐based algorithms to produce a highly reliable machine‐learning algorithm. The algorithm is run on the benchmark “MONK′s data sets”. Compares the results of standard machine learning algorithms such as the ID and AQ families of algorithms. The algorithm is also run on the breast cancer data set and the results are compared with C4.5 algorithm results.
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