Effects of domain characteristics on instance-based learning algorithms
نویسندگان
چکیده
منابع مشابه
Effects of domain characteristics on instance-based learning algorithms
This paper presents average-case analyses of instance-based learning algorithms. The algorithms analyzed employ a variant of k-nearest neighbor classi-er (k-NN). Our analysis deals with a monotone m-of-n target concept with irrelevant attributes, and handles three types of noise: relevant attribute noise, irrelevant attribute noise, and class noise. We formally represent the expected classi-cat...
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.......................................................................................................................... iii Acknowledgements ....................................................................................................... iv Dedication........................................................................................................................ v Table of
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ژورنال
عنوان ژورنال: Theoretical Computer Science
سال: 2003
ISSN: 0304-3975
DOI: 10.1016/s0304-3975(02)00424-3