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Does It Make Sense to Develop New Feature Selection Methods?

Typ:
Research report
Name of edition:
Research Report
Article number:
2193
Publisher:
ÚTIA AV ČR
Serie:
Praha
Year:
2007
Keywords:
feature selection, subset search, search methods, performanc
Anotation:
One of hot topics discussed recently in relation to pattern recognition techniques is the question of actual performance of modern feature selection methods. Feature selection has been a highly active area of research in recent years due to its potential to improve both the performance and economy of automatic decision systems in various applicational fields, with medical diagnosis being among the most prominent. Feature selection may also improve the performance of classifiers learned from limited data, or contribute to model interpretability. The number of available methods and methodologies has grown rapidly while promising important improvements. Yet recently many authors put this development in question, claiming that simpler older tools show to be actually better than complex modern ones -- which, despite promises, are claimed to actually fail in real-world applications.
 
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