Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Victor J. Rayward-Smith"'
Autor:
Catherine Butchart, Firat Ismailoglu, Claire J Lunt, Roy L. Soiza, Victor J. Rayward-Smith, Phyo K. Myint, Yogish Pai, Patrick Musonda
Publikováno v:
Archives of Gerontology and Geriatrics, 56(1), 188-191. Elsevier Ireland Ltd
Current demographic trends suggest that there will be increasing numbers of older people in the future. Relatively little information is available regarding factors which influence mortality in the acutely unwell oldest old. This study uses the CART
Publikováno v:
Journal of Mathematical Modelling and Algorithms. 10:57-78
Clustering remains one of the most difficult challenges in data mining. This paper proposes a new algorithm, CLAM, using a hybrid metaheuristic between VNS and Tabu Search to solve the problem of k-medoid clustering. The new technique is compared to
Publikováno v:
Computers & Operations Research. 35:3298-3310
The problem of minimising the overall completion time for the two-machine flow shop problem with unit execution time (UET) tasks and arbitrary time delays is known to be unary NP-hard. Two heuristic algorithms to solve this problem along with their w
Autor:
Victor J. Rayward-Smith
Publikováno v:
Computational Statistics & Data Analysis. 51:3968-3982
Correlation is usually used in the context of real-valued sequences but, in data mining, the values of fields may be of various types-real, nominal or ordinal. Techniques for measuring correlation between any two sequences of data are reviewed, regar
Publikováno v:
Applied Intelligence. 24:219-226
k-means is traditionally viewed as an algorithm for the unsupervised clustering of a heterogeneous population into a number of more homogeneous groups of objects. However, it is not necessarily guaranteed to group the same types (classes) of objects
Publikováno v:
Journal of Mathematical Modelling and Algorithms. 5:475-504
Previous research has resulted in a number of different algorithms for rule discovery. Two approaches discussed here, the ‘all-rules’ algorithm and multi-objective metaheuristics, both result in the production of a large number of partial classif
Publikováno v:
European Journal of Operational Research. 169:898-917
In this paper, we present an application of multi-objective metaheuristics to the field of data mining. We introduce the data mining task of nugget discovery (also known as partial classification) and show how the multi-objective metaheuristic algori
Autor:
Jan-Jaap Wesselink, Ian N. Roberts, Victor J. Rayward-Smith, Jo Dicks, Stephen A. James, Beatriz de la Iglesia
Publikováno v:
Bioinformatics. 18:1004-1010
Motivation: Yeasts are often still identified with physiological growth tests, which are both time consuming and unsuitable for detection of a mixture of organisms. Hence, there is a need for molecular methods to identify yeast species. Results: A ha
Publikováno v:
Information and Software Technology. 43:883-890
Companies developing and maintaining complex software systems need to determine the features that should be added to their system as part of the next release. They will wish to select these features to ensure the demands of their client base are sati
Publikováno v:
Artificial Intelligence in Medicine. 22:215-231
This paper describes the analysis of a database of diabetic patients' clinical records and death certificates. The objective of the study was to find rules that describe associations between observations made of patients at their first visit to the h