TY - GEN
T1 - New strategies for evaluating the performance of typical testor algorithms
AU - Alba, Eduardo
AU - Guilcapi, Diego
AU - Ibarra, Julio
PY - 2012
Y1 - 2012
N2 - Typical testors have been used in feature selection and supervised classification problems in the logical combinatorial pattern recognition. Several algorithms have been used to find the set of all typical testors of a basic matrix. This algorithms are based on different heuristics. There is no doubt these algorithms find the set of all typical testors. However, the time spent on this search strategies, differs between them. Due to size of this set, the search time is a critical factor. There is not a standard procedure to evaluate the time performance of typical testors algorithms. In this paper we introduce a strategy to solve this problem through a new set of test matrices. These test matrices have the property that the set's cardinality of all typical testors is known in advance.
AB - Typical testors have been used in feature selection and supervised classification problems in the logical combinatorial pattern recognition. Several algorithms have been used to find the set of all typical testors of a basic matrix. This algorithms are based on different heuristics. There is no doubt these algorithms find the set of all typical testors. However, the time spent on this search strategies, differs between them. Due to size of this set, the search time is a critical factor. There is not a standard procedure to evaluate the time performance of typical testors algorithms. In this paper we introduce a strategy to solve this problem through a new set of test matrices. These test matrices have the property that the set's cardinality of all typical testors is known in advance.
KW - Logical combinatorial PR
KW - feature selection
KW - test matrices
KW - testor theory
KW - typical testors algorithms
UR - https://www.scopus.com/pages/publications/84865580951
U2 - 10.1007/978-3-642-33275-3_100
DO - 10.1007/978-3-642-33275-3_100
M3 - Contribución a la conferencia
AN - SCOPUS:84865580951
SN - 9783642332746
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 813
EP - 820
BT - Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Proceedings
T2 - 17th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2012
Y2 - 3 September 2012 through 6 September 2012
ER -