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Physical Sciences and Mathematics Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Explicit Connections Between Longitudinal Data Analysis And Kernel Machines, N D. Pearce, M. P. Wand
Explicit Connections Between Longitudinal Data Analysis And Kernel Machines, N D. Pearce, M. P. Wand
Faculty of Informatics - Papers (Archive)
Two areas of research - longitudinal data analysis and kernel machines - have large, but mostly distinct, literatures. This article shows explicitly that both fields have much in common with each other. In particular, many popular longitudinal data fitting procedures are special types of kernel machines. These connections have the potential to provide fruitful cross-fertilization between longitudinal data analytic and kernel machine methodology.
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Clustering, Classification And Explanatory Rules From Harmonic Monitoring Data, Ali Asheibi, David A. Stirling, Danny Sutanto, D A. Robinson
Faculty of Informatics - Papers (Archive)
A method based on the successful AutoClass (Cheeseman & Stutz, 1996) and the Snob research programs (Wallace & Dowe, 1994); (Baxter & Wallace, 1996) has been chosen for our research work on harmonic classification. The method utilizes mixture models (McLachlan, 1992) as a representation of the formulated clusters. This research is principally based on the formation of such mixture models (typically based on Gaussian distributions) through a Minimum Message Length (MML) encoding scheme (Wallace & Boulton, 1968). During the formation of such mixture models the various derivative tools (algorithms) allow for the automated selection of the number of clusters and …
Learning Pattern Classification Tasks With Imbalanced Data Sets, Son Lam Phung, Abdesselam Bouzerdoum, Giang Hoang Nguyen
Learning Pattern Classification Tasks With Imbalanced Data Sets, Son Lam Phung, Abdesselam Bouzerdoum, Giang Hoang Nguyen
Faculty of Informatics - Papers (Archive)
This chapter is concerned with the class imbalance problem, which has been recognised as a crucial problem in machine learning and data mining. The problem occurs when there are significantly fewer training instances of one class compared to another class.