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KDD
2012
ACM
178views Data Mining» more  KDD 2012»
11 years 10 months ago
Mining emerging patterns by streaming feature selection
Building an accurate emerging pattern classifier with a highdimensional dataset is a challenging issue. The problem becomes even more difficult if the whole feature space is unava...
Kui Yu, Wei Ding 0003, Dan A. Simovici, Xindong Wu
KDD
2010
ACM
197views Data Mining» more  KDD 2010»
13 years 5 months ago
Semi-supervised feature selection for graph classification
The problem of graph classification has attracted great interest in the last decade. Current research on graph classification assumes the existence of large amounts of labeled tra...
Xiangnan Kong, Philip S. Yu
CIKM
2011
Springer
12 years 7 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han
CIARP
2007
Springer
14 years 1 months ago
Generalizing Dissimilarity Representations Using Feature Lines
A crucial issue in dissimilarity-based classification is the choice of the representation set. In the small sample case, classifiers capable of a good generalization and the inje...
Mauricio Orozco-Alzate, Robert P. W. Duin, C&eacut...
ICML
2010
IEEE
13 years 8 months ago
From Transformation-Based Dimensionality Reduction to Feature Selection
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy