Title :
The development of Holte´s 1R classifier
Author :
Nevill-Manning, C.G. ; Holmes, Geoffrey ; Witten, Ian H.
Author_Institution :
Dept. of Comput. Sci., Waikato Univ., Hamilton, New Zealand
Abstract :
The 1R machine learning scheme (Holte, 1993) is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the method and discusses two aspects of the algorithm that bear further analysis: the way, that intervals are formed when discretizing continuously-valued attributes; and the way missing values are treated. We then show how the algorithm can be extended to avoid a problem endemic to most practical machine learning algorithms-their frequent dismissal of an attribute as irrelevant when in fact it is highly relevant when combined with other attributes
Keywords :
database management systems; inference mechanisms; learning by example; uncertainty handling; 1R classifier; 1R machine learning scheme; algorithm; continuously-valued attributes; datasets; learning by example; machine learning algorithms; missing values; relevant attributes; Accuracy; Algorithm design and analysis; Computer science; Filters; Learning systems; Machine learning; Machine learning algorithms; Quantization; Rain; Testing;
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-7174-2
DOI :
10.1109/ANNES.1995.499480
