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ALGORITHMICA
2006
74views more  ALGORITHMICA 2006»
13 years 9 months ago
Parallelizing Feature Selection
Classification is a key problem in machine learning/data mining. Algorithms for classification have the ability to predict the class of a new instance after having been trained on...
Jerffeson Teixeira de Souza, Stan Matwin, Nathalie...
GECCO
2003
Springer
160views Optimization» more  GECCO 2003»
14 years 2 months ago
Using Genetic Algorithms for Data Mining Optimization in an Educational Web-Based System
This paper presents an approach for classifying students in order to predict their final grade based on features extracted from logged data in an education web-based system. A comb...
Behrouz Minaei-Bidgoli, William F. Punch
MM
2006
ACM
142views Multimedia» more  MM 2006»
14 years 2 months ago
Large-scale video retrieval via semantic classification
ons for this project. Most recent ones are listed at the end of this abstract. In the future, feature selection will be integrated in the multi-class EM algorithm to improve the pe...
Hangzai Luo, Jianping Fan
CG
2010
Springer
13 years 7 months ago
The effect of task on classification accuracy: Using gesture recognition techniques in free-sketch recognition
Generating, grouping, and labeling free-sketch data is a difficult and time-consuming task for both user study participants and researchers. To simplify this process for both part...
M. Field, S. Gordon, Eric Jeffrey Peterson, R. Rob...
CIKM
2008
Springer
13 years 11 months ago
Error-driven generalist+experts (edge): a multi-stage ensemble framework for text categorization
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
Jian Huang 0002, Omid Madani, C. Lee Giles