Scheduling a set of n jobs on a single machine so as to minimize the completion time variance is a well-known NP-hard problem. In this paper, we propose a sequence, which can be constructed in O(n log n) time, as a solution for the problem. Our primary concern is to establish the asymptotical optima
Asymptotical optimality in cluster analysis
β Scribed by Kharin, Yurij S. ;Zhuk, Eugene E.
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 97 KB
- Volume
- 15
- Category
- Article
- ISSN
- 8755-0024
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β¦ Synopsis
The problem of optimality and performance evaluation for cluster analysis procedures is investigated. For the situations where the classes are described by known or unknown prior probabilities and regular probability density functions with unknown parameters the asymptotic expansions of classiΓΏcation error probability are constructed. The results are illustrated for the case of well-known Fisher classiΓΏcation model.
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