Pfahringer, B. (1995). Practical Uses of the Minimum Description Length Principle in Inductive Learning. Ph.D. thesis, Technische Universitat Wien. Home/Search Document Details and Download
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Integrative Windowing - Fürnkranz (1998) (Correct)
....usually easily found from small random samples of the dataset. On the other hand, rules 1 and 2, and in particular 6 and 7 cover a significantly smaller number 4. Note, however, that not all different positions form a different feature vector with the specified features as has been pointed out by Pfahringer (1995). F urnkranz of examples. In order to obtain enough examples for learning these rules, one has to take a much larger random sample of the data. 5 This problem is closely related to the small disjuncts problem discussed by Holte, Acker, and Porter (1989) How does windowing deal with this ....
Pfahringer, B. (1995). Practical Uses of the Minimum Description Length Principle in Inductive Learning. Ph.D. thesis, Technische Universitat Wien.
Compression-based Pruning of Decision Lists - Pfahringer (1997) (Correct)
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Pfahringer B.: Practical Uses of the Minimum Description Length Principle in Inductive Learning, Institut fur Med.Kybernetik u. AI, Technische Universitat Wien, Dissertation, 1995.
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