Titlebook: Discovery Science; Third International Setsuo Arikawa,Shinichi Morishita Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 200

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Studies in the Sociology of Populationare represented in the form of tables and many rules are represented in the form of functions. A simple greedy algorithm has been known as an approximation algorithm for this problem. In this algorithm, the original problem is reduced to the set cover problem and a well-known greedy algorithm for th

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Cellular Aging / Replicative Senescencee), to name a few. Thus, efficiently finding characteristic substructures in a graph will be a useful technique in many important KDD/ML applications. However, graph pattern matching is a hard problem. We propose a machine learning technique called Graph- Based Induction (GBI) that efficiently extra

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https://doi.org/10.1007/978-3-642-59916-3rks by another writer as ., to find expressions that appear frequently in the positive examples but do not so in the negative examples. It is considered as a special case of . from textual data, in which only . are considered. One reasonable approach is to create a list of substrings arranged in the

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