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RSFDGRC
2005
Springer
190views Data Mining» more  RSFDGRC 2005»
15 years 10 months ago
Finding Rough Set Reducts with SAT
Abstract. Feature selection refers to the problem of selecting those input features that are most predictive of a given outcome; a problem encountered in many areas such as machine...
Richard Jensen, Qiang Shen, Andrew Tuson
GECCO
2006
Springer
214views Optimization» more  GECCO 2006»
15 years 8 months ago
A new discrete particle swarm algorithm applied to attribute selection in a bioinformatics data set
Many data mining applications involve the task of building a model for predictive classification. The goal of such a model is to classify examples (records or data instances) into...
Elon S. Correa, Alex Alves Freitas, Colin G. Johns...
152
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CORR
2010
Springer
149views Education» more  CORR 2010»
15 years 5 months ago
Using Rough Set and Support Vector Machine for Network Intrusion Detection
The main function of IDS (Intrusion Detection System) is to protect the system, analyze and predict the behaviors of users. Then these behaviors will be considered an attack or a ...
Rung Ching Chen, Kai-Fan Cheng, Chia-Fen Hsieh
PAMI
2006
243views more  PAMI 2006»
15 years 5 months ago
Dynamical Statistical Shape Priors for Level Set-Based Tracking
In recent years, researchers have proposed to introduce statistical shape knowledge into level set based segmentation methods in order to cope with insufficient low-level informati...
Daniel Cremers
KAIS
2010
144views more  KAIS 2010»
15 years 3 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz