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CIARP
2010
Springer
13 years 10 months ago
Improving the Dynamic Hierarchical Compact Clustering Algorithm by Using Feature Selection
Abstract. Feature selection has improved the performance of text clustering. In this paper, a local feature selection technique is incorporated in the dynamic hierarchical compact ...
Reynaldo Gil-García, Aurora Pons-Porrata
SAC
2008
ACM
13 years 11 months ago
Towards automatic feature vector optimization for multimedia applications
We systematically evaluate a recently proposed method for unsupervised discrimination power analysis for feature selection and optimization in multimedia applications. A series of...
Tobias Schreck, Dieter W. Fellner, Daniel A. Keim
PRL
2007
168views more  PRL 2007»
13 years 11 months ago
Competitive baseline methods set new standards for the NIPS 2003 feature selection benchmark
We used the datasets of the NIPS 2003 challenge on feature selection as part of the practical work of an undergraduate course on feature extraction. The students were provided wit...
Isabelle Guyon, Jiwen Li, Theodor Mader, Patrick A...
PRL
2007
180views more  PRL 2007»
13 years 11 months ago
Feature selection based on rough sets and particle swarm optimization
: We propose a new feature selection strategy based on rough sets and Particle Swarm Optimization (PSO). Rough sets has been used as a feature selection method with much success, b...
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xi...
ESWA
2008
141views more  ESWA 2008»
13 years 11 months ago
Classifier design with feature selection and feature extraction using layered genetic programming
This paper proposes a novel method called FLGP to construct a classifier device of capability in feature selection and feature extraction. FLGP is developed with layered genetic p...
Jung-Yi Lin, Hao-Ren Ke, Been-Chian Chien, Wei-Pan...
PAMI
2002
136views more  PAMI 2002»
13 years 11 months ago
Unsupervised Feature Selection Using Feature Similarity
Pabitra Mitra, C. A. Murthy, Sankar K. Pal
IDA
2002
Springer
13 years 11 months ago
Evolutionary model selection in unsupervised learning
Feature subset selection is important not only for the insight gained from determining relevant modeling variables but also for the improved understandability, scalability, and pos...
YongSeog Kim, W. Nick Street, Filippo Menczer
BMCBI
2004
167views more  BMCBI 2004»
13 years 11 months ago
Feature selection for splice site prediction: A new method using EDA-based feature ranking
Background: The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Oth...
Yvan Saeys, Sven Degroeve, Dirk Aeyels, Pierre Rou...
BMCBI
2004
205views more  BMCBI 2004»
13 years 11 months ago
A combinational feature selection and ensemble neural network method for classification of gene expression data
Background: Microarray experiments are becoming a powerful tool for clinical diagnosis, as they have the potential to discover gene expression patterns that are characteristic for...
Bing Liu, Qinghua Cui, Tianzi Jiang, Songde Ma
BC
2004
133views more  BC 2004»
13 years 11 months ago
Coevolution of active vision and feature selection
We show that complex visual tasks, such as position- and size-invariant shape recognition and navigation in the environment, can be tackled with simple architectures generated by a...
Dario Floreano, Toshifumi Kato, Davide Marocco, Er...