TY - GEN
T1 - Parallelization Algorithm for the Calculation of Typical Testors Based on YYC
AU - Soria-Salgado, Ariana
AU - Ibarra-Fiallo, Julio
AU - Alba-Cabrera, Eduardo
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - In the present work, a new method is proposed to find typical testors, which helps reduce the number of features needed to carry out classification processes. Using the strategy of divide and conquer, we divide a basic matrix into blocks, then we find the typical testors of the defined blocks. To find the typical testors of the complete basic matrix, unions between the elements of these sets obtained from the blocks are tested. A criterion is developed to determine when the unions of typical testors of blocks form typical testors of the complete matrix. The performance of the method is evaluated using synthetic matrices. The execution time of the method in parallel and sequential versions was compared and contrasted with the YYC algorithm used for the complete basic matrix. Finally, its performance is analyzed in a real database obtained from the UCI Repository.
AB - In the present work, a new method is proposed to find typical testors, which helps reduce the number of features needed to carry out classification processes. Using the strategy of divide and conquer, we divide a basic matrix into blocks, then we find the typical testors of the defined blocks. To find the typical testors of the complete basic matrix, unions between the elements of these sets obtained from the blocks are tested. A criterion is developed to determine when the unions of typical testors of blocks form typical testors of the complete matrix. The performance of the method is evaluated using synthetic matrices. The execution time of the method in parallel and sequential versions was compared and contrasted with the YYC algorithm used for the complete basic matrix. Finally, its performance is analyzed in a real database obtained from the UCI Repository.
KW - accuracy
KW - classification
KW - computational efficiency
KW - neural networks
KW - pattern recognition
KW - time execution
KW - typical testors
UR - http://www.scopus.com/inward/record.url?scp=85187662118&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-45642-8_47
DO - 10.1007/978-3-031-45642-8_47
M3 - Contribución a la conferencia
AN - SCOPUS:85187662118
SN - 9783031456411
T3 - Lecture Notes in Networks and Systems
SP - 477
EP - 489
BT - Information Systems and Technologies - WorldCIST 2023
A2 - Rocha, Alvaro
A2 - Adeli, Hojjat
A2 - Dzemyda, Gintautas
A2 - Moreira, Fernando
A2 - Colla, Valentina
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th World Conference on Information Systems and Technologies, WorldCIST 2023
Y2 - 4 April 2023 through 6 April 2023
ER -