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|Title:||Mitotic classes||Authors:||Jain, S.
|Issue Date:||2007||Citation:||Jain, S.,Stephan, F. (2007). Mitotic classes. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4539 LNAI : 218-232. ScholarBank@NUS Repository.||Abstract:||For the natural notion of splitting classes into two disjoint subclasses via a recursive classifier working on texts, the question is addressed how these splittings can look in the case of learnable classes. Here the strength of the classes is compared using the strong and weak reducibility from intrinsic complexity. It is shown that, for explanatorily learnable classes, the complete classes are also mitotic with respect to weak and strong reducibility, respectively. But there is a weak complete class which cannot be split into two classes which are of the same complexity with respect to strong reducibility. It is shown that for complete classes for behaviourally correct learning, one half of each splitting is complete for this learning notion as well. Furthermore, it is shown that explanatorily learnable and recursively enumerable classes always have a splitting into two incomparable classes; this gives an inductive inference counterpart of Sacks Splitting Theorem from recursion theory. © Springer-Verlag Berlin Heidelberg 2007.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/43293||ISBN:||9783540729259||ISSN:||03029743|
|Appears in Collections:||Staff Publications|
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