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» Margin based feature selection - theory and algorithms
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MCS
2007
Springer
14 years 1 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
EWCBR
2006
Springer
13 years 11 months ago
Rough Set Feature Selection Algorithms for Textual Case-Based Classification
Feature selection algorithms can reduce the high dimensionality of textual cases and increase case-based task performance. However, conventional algorithms (e.g., information gain)...
Kalyan Moy Gupta, David W. Aha, Philip Moore
IJON
2008
121views more  IJON 2008»
13 years 7 months ago
Locality sensitive semi-supervised feature selection
In many computer vision tasks like face recognition and image retrieval, one is often confronted with high-dimensional data. Procedures that are analytically or computationally ma...
Jidong Zhao, Ke Lu, Xiaofei He
CSIE
2009
IEEE
14 years 2 months ago
Evaluating Clustering Algorithms: Cluster Quality and Feature Selection in Content-Based Image Clustering
The paper presents an evaluation of four clustering algorithms: k-means, average linkage, complete linkage, and Ward’s method, with the latter three being different hierarchical...
Mesfin Sileshi, Björn Gambäck
CDC
2008
IEEE
14 years 2 months ago
Shannon meets Bellman: Feature based Markovian models for detection and optimization
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
Sean P. Meyn, George Mathew