TY - GEN
T1 - Bayesian top scoring pairs for feature selection
AU - Arslan, Emre
AU - Braga-Neto, Ulisses M.
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/4/10
Y1 - 2018/4/10
N2 - We propose a novel feature selection approach based on the Bayesian Top Scoring Pairs (BTSP) method. We compare its performance against well-known feature selection methods, under SVM, k-NN and NB classification rules, by means of an extensive numerical experiment using real gene-expression data sets. Results demonstrate the promise of the BTSP feature selection approach in the analysis of high-dimensional biological data.
AB - We propose a novel feature selection approach based on the Bayesian Top Scoring Pairs (BTSP) method. We compare its performance against well-known feature selection methods, under SVM, k-NN and NB classification rules, by means of an extensive numerical experiment using real gene-expression data sets. Results demonstrate the promise of the BTSP feature selection approach in the analysis of high-dimensional biological data.
KW - Bayesian Top Scoring Pairs
KW - Dimensionality Reduction
KW - Feature Selection
UR - http://www.scopus.com/inward/record.url?scp=85050958149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050958149&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2017.8335365
DO - 10.1109/ACSSC.2017.8335365
M3 - Conference contribution
AN - SCOPUS:85050958149
T3 - Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
SP - 387
EP - 391
BT - Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
A2 - Matthews, Michael B.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Y2 - 29 October 2017 through 1 November 2017
ER -