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» Memetic Algorithms for Feature Selection on Microarray Data
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ISNN
2011
Springer
12 years 10 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
IDEAL
2004
Springer
14 years 1 months ago
Prediction of Implicit Protein-Protein Interaction by Optimal Associative Feature Mining
Proteins are known to perform a biological function by interacting with other proteins or compounds. Since protein–protein interaction is intrinsic to most cellular processes, pr...
Jae-Hong Eom, Jeong Ho Chang, Byoung-Tak Zhang
ICDE
2008
IEEE
158views Database» more  ICDE 2008»
14 years 9 months ago
CARE: Finding Local Linear Correlations in High Dimensional Data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
Xiang Zhang, Feng Pan, Wei Wang
MCS
2007
Springer
14 years 1 months ago
Selecting Diversifying Heuristics for Cluster Ensembles
Abstract. Cluster ensembles are deemed to be better than single clustering algorithms for discovering complex or noisy structures in data. Various heuristics for constructing such ...
Stefan Todorov Hadjitodorov, Ludmila I. Kuncheva
ADC
2006
Springer
120views Database» more  ADC 2006»
14 years 1 months ago
Approximate data mining in very large relational data
In this paper we discuss eNERF, an extended version of non-Euclidean relational fuzzy c-means (NERFCM) for approximate clustering in very large (unloadable) relational data. The e...
James C. Bezdek, Richard J. Hathaway, Christopher ...