TY - GEN
T1 - Authoritative citation KNN learning with noisy training datasets
AU - Bernadt, Joseph
AU - Soh, Leen Kiat
N1 - Funding Information:
Our research was supported by the Telethon Foundation , Italy (grant GGP19007 ), ERC Advanced grant FP7-3222424 , and a grant from the NRJ-Institut de France (to M.Z.); Associazione Luigi Comini ONLUS ; and a core grant from the Medical Research Council , UK (grant MC_UU_00015/5 ). We are grateful to the MRC-Laboratory of Molecular Biology Electron Microscopy Facility for access to their resources. We thank Ana B. Cortés at UPO for support in CoQ measurements and Dr. Erika Fernandez-Vizarra, Dr. Aurora Gomez-Duran, and Pedro Pinheiro for their help and advice. We are grateful to Dr. Silvia Armelloni, the Renal Research Laboratory, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy for sharing the protocol to isolate podocytes.
PY - 2004
Y1 - 2004
N2 - In this paper, we investigate the effectiveness of Citation K-Nearest Neighbors (KNN) learning with noisy training datasets. We devise an authority measure associated with each training instance that changes based on the outcome of Citation KNN classification. We show that by modifying only the authority measures, the classification accuracy by Citation KNN improves significantly in a variety of datasets with different noise levels. Also, by analyzing the authority measures, we are able to identify and correct noisy training instances.
AB - In this paper, we investigate the effectiveness of Citation K-Nearest Neighbors (KNN) learning with noisy training datasets. We devise an authority measure associated with each training instance that changes based on the outcome of Citation KNN classification. We show that by modifying only the authority measures, the classification accuracy by Citation KNN improves significantly in a variety of datasets with different noise levels. Also, by analyzing the authority measures, we are able to identify and correct noisy training instances.
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M3 - Conference contribution
AN - SCOPUS:12744260611
SN - 1932415335
SN - 9781932415339
T3 - Proceedings of the International Conference on Artificial Intelligence, IC-AI'04
SP - 916
EP - 921
BT - Proceedings of the International Conference on Artificial Intelligence, IC-AI'04 and Proceedings of the International Conference on Machine Learning; Models, Technologies and Applications, MLMTA'04)
A2 - Arabnia, H.R.
A2 - Youngsong, M.
T2 - Proceedings of the International Conference on Artificial Intelligence, IC-AI'04
Y2 - 21 June 2004 through 24 June 2004
ER -