TY - JOUR
T1 - RoPM
T2 - An Algorithm for Computing Typical Testors Based on Recursive Reductions of the Basic Matrix
AU - Gomez, Joel Pino
AU - Montero, Fidel Ernesto Hernandez
AU - Sotelo, Joel Charles
AU - Mancilla, Julio Cesar Gomez
AU - Rey, Yenny Villuendas
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2021
Y1 - 2021
N2 - Feature selection plays an important role in pattern recognition and smart computing. The full set of typical testors constitutes a useful tool for solving feature selection problems, especially those problems in which the objects are described by both quantitative and qualitative features. However, finding the typical testors involves a high computational cost. That is why even the most efficient methods become unsuitable to solve some problems. In this work, a new algorithm was introduced in order to reduce the long runtimes involved in the search of typical testors. The performance of the proposed algorithm was evaluated by means of several tests, which use both real-world and simulation data. MATLAB and Java language on Eclipse SDK platform were used to build the simulation dataset and to perform the tests, respectively. The runtimes achieved by the proposed algorithm were significantly shorter than those obtained by fast-BR and GCreduct (the two fastest algorithms) mainly when the latter ones exhibited excessively long runtimes.
AB - Feature selection plays an important role in pattern recognition and smart computing. The full set of typical testors constitutes a useful tool for solving feature selection problems, especially those problems in which the objects are described by both quantitative and qualitative features. However, finding the typical testors involves a high computational cost. That is why even the most efficient methods become unsuitable to solve some problems. In this work, a new algorithm was introduced in order to reduce the long runtimes involved in the search of typical testors. The performance of the proposed algorithm was evaluated by means of several tests, which use both real-world and simulation data. MATLAB and Java language on Eclipse SDK platform were used to build the simulation dataset and to perform the tests, respectively. The runtimes achieved by the proposed algorithm were significantly shorter than those obtained by fast-BR and GCreduct (the two fastest algorithms) mainly when the latter ones exhibited excessively long runtimes.
KW - Algorithm
KW - feature selection
KW - runtimes
KW - typical testors
UR - http://www.scopus.com/inward/record.url?scp=85115147772&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2021.3112385
DO - 10.1109/ACCESS.2021.3112385
M3 - Artículo
AN - SCOPUS:85115147772
SN - 2169-3536
VL - 9
SP - 128220
EP - 128232
JO - IEEE Access
JF - IEEE Access
ER -