TY - GEN
T1 - Model selection with PLANN-CR-ARD
AU - Arsene, Corneliu T C
AU - Lisboa, Paulo J.
AU - Biganzoli, Elia
PY - 2011
Y1 - 2011
N2 - This paper presents a new compensation mechanism to be used with a Partial Logistic Artificial Neural Network for Competing Risks with Automatic Relevance Determination (PLANN-CR-ARD) and tested comprehensibly on a real breast cancer dataset with excellent convergence properties and numerical stability for the non-linear model. The Model Selection is implemented for the PLANN-CR-ARD model, benefiting from a scaling of the prior error term which together with the data error term forms the total error function that is optimized. The PLANN-CR-ARD proves to be an excellent prognostic tool that can be used in regression analysis tasks such as the survival analysis of cancer datasets.
AB - This paper presents a new compensation mechanism to be used with a Partial Logistic Artificial Neural Network for Competing Risks with Automatic Relevance Determination (PLANN-CR-ARD) and tested comprehensibly on a real breast cancer dataset with excellent convergence properties and numerical stability for the non-linear model. The Model Selection is implemented for the PLANN-CR-ARD model, benefiting from a scaling of the prior error term which together with the data error term forms the total error function that is optimized. The PLANN-CR-ARD proves to be an excellent prognostic tool that can be used in regression analysis tasks such as the survival analysis of cancer datasets.
KW - Artificial Neural Networks
KW - Competing Risks
KW - Convergence properties
KW - Model Selection
KW - PLANN-CR-ARD
UR - http://www.scopus.com/inward/record.url?scp=79957936804&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79957936804&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-21498-1_27
DO - 10.1007/978-3-642-21498-1_27
M3 - Conference contribution
AN - SCOPUS:79957936804
SN - 9783642214974
VL - 6692 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 210
EP - 219
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
T2 - 11th International Work-Conference on on Artificial Neural Networks, IWANN 2011
Y2 - 8 June 2011 through 10 June 2011
ER -