TY - GEN
T1 - Optimized associative memories for feature selection
AU - Aldape-Pérez, Mario
AU - Yáñez-Márquez, Cornelio
AU - Argüelles-Cruz, Amadeo José
PY - 2007
Y1 - 2007
N2 - Performance in most pattern classifiers is improved when redundant or irrelevant features are removed, however, this is mainly achieved by high demanding computational methods or successive classifiers construction. This paper shows how Associative Memories can be used to get a mask value which represents a subset of features that clearly identifies irrelevant or redundant information for classification purposes, therefore, classification accuracy is improved while significant computational costs in the learning phase are reduced. An optimal subset of features allows register size optimization, which contributes not only to significant power savings but to a smaller amount of synthesized logic, furthermore, improved hardware architectures are achieved due to functional units size reduction, as a result, it is possible to implement parallel and cascade schemes for pattern classifiers on the same ASIC.
AB - Performance in most pattern classifiers is improved when redundant or irrelevant features are removed, however, this is mainly achieved by high demanding computational methods or successive classifiers construction. This paper shows how Associative Memories can be used to get a mask value which represents a subset of features that clearly identifies irrelevant or redundant information for classification purposes, therefore, classification accuracy is improved while significant computational costs in the learning phase are reduced. An optimal subset of features allows register size optimization, which contributes not only to significant power savings but to a smaller amount of synthesized logic, furthermore, improved hardware architectures are achieved due to functional units size reduction, as a result, it is possible to implement parallel and cascade schemes for pattern classifiers on the same ASIC.
KW - Feature selection
KW - Masking techniques
KW - Pattern classifier
KW - Supervised learning
UR - http://www.scopus.com/inward/record.url?scp=38149015465&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-72847-4_56
DO - 10.1007/978-3-540-72847-4_56
M3 - Contribución a la conferencia
SN - 9783540728467
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 435
EP - 442
BT - Pattern Recognition and Image Analysis - Third Iberian Conference, IbPRIA 2007, Proceedings
PB - Springer Verlag
T2 - 3rd Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2007
Y2 - 6 June 2007 through 8 June 2007
ER -