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ICAI
2010
14 years 7 months ago
An Efficient Sequential Covering Algorithm for Explaining Subsets of Data
Given a subset of data that differs from the rest, a user often wants an explanation as to why this is the case. For instance, in a database of flights, a user may want to understa...
Matthew Michelson, Sofus A. Macskassy
GECCO
2003
Springer
15 years 3 months ago
Mining Comprehensible Clustering Rules with an Evolutionary Algorithm
In this paper, we present a novel evolutionary algorithm, called NOCEA, which is suitable for Data Mining (DM) clustering applications. NOCEA evolves individuals that consist of a ...
Ioannis A. Sarafis, Philip W. Trinder, Ali M. S. Z...
BMCBI
2005
80views more  BMCBI 2005»
14 years 9 months ago
Sample phenotype clusters in high-density oligonucleotide microarray data sets are revealed using Isomap, a nonlinear algorithm
Background: Life processes are determined by the organism's genetic profile and multiple environmental variables. However the interaction between these factors is inherently ...
Kevin Dawson, Raymond L. Rodriguez, Wasyl Malyj
IBPRIA
2003
Springer
15 years 3 months ago
Incrementally Assessing Cluster Tendencies with a Maximum Variance Cluster Algorithm
A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the ...
Krzysztof Rzadca, Francesc J. Ferri
ISNN
2007
Springer
15 years 4 months ago
Extensions of Manifold Learning Algorithms in Kernel Feature Space
Manifold learning algorithms have been proven to be capable of discovering some nonlinear structures. However, it is hard for them to extend to test set directly. In this paper, a ...
Yaoliang Yu, Peng Guan, Liming Zhang