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KDD
2008
ACM
264views Data Mining» more  KDD 2008»
14 years 10 months ago
Stable feature selection via dense feature groups
Many feature selection algorithms have been proposed in the past focusing on improving classification accuracy. In this work, we point out the importance of stable feature selecti...
Lei Yu, Chris H. Q. Ding, Steven Loscalzo
ICDM
2010
IEEE
228views Data Mining» more  ICDM 2010»
13 years 7 months ago
Multi-label Feature Selection for Graph Classification
Nowadays, the classification of graph data has become an important and active research topic in the last decade, which has a wide variety of real world applications, e.g. drug acti...
Xiangnan Kong, Philip S. Yu
CIDM
2009
IEEE
14 years 4 months ago
Ensemble member selection using multi-objective optimization
— Both theory and a wealth of empirical studies have established that ensembles are more accurate than single predictive models. Unfortunately, the problem of how to maximize ens...
Tuve Löfström, Ulf Johansson, Henrik Bos...
PRL
2010
159views more  PRL 2010»
13 years 8 months ago
Creating diverse nearest-neighbour ensembles using simultaneous metaheuristic feature selection
The nearest-neighbour (1NN) classifier has long been used in pattern recognition, exploratory data analysis, and data mining problems. A vital consideration in obtaining good res...
Muhammad Atif Tahir, Jim E. Smith
ISMIS
2005
Springer
14 years 3 months ago
Scalable Inductive Learning on Partitioned Data
With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, sc...
Qijun Chen, Xindong Wu, Xingquan Zhu