Classifier performance estimation under the constraint of a finite sample size: Resampling schemes applied to neural network classifiers
- 30 April 2008
- journal article
- Published by Elsevier BV in Neural Networks
- Vol. 21 (2-3), 476-483
- https://doi.org/10.1016/j.neunet.2007.12.012
Abstract
No abstract availableKeywords
This publication has 6 references indexed in Scilit:
- Classifier Performance Estimation Under the Constraint of a Finite Sample Size: Resampling Schemes Applied to Neural Network Classifiers2007 International Joint Conference on Neural Networks, 2007
- Comparison of Non-Parametric Methods for Assessing Classifier Performance in Terms of ROC ParametersPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2005
- Classifier design for computer‐aided diagnosis: Effects of finite sample size on the mean performance of classical and neural network classifiersMedical Physics, 1999
- Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed dataStatistics in Medicine, 1998
- Effects of sample size in classifier designIEEE Transactions on Pattern Analysis and Machine Intelligence, 1989
- Estimating the Error Rate of a Prediction Rule: Improvement on Cross-ValidationJournal of the American Statistical Association, 1983