Gavin C Cawley
Gavin C Cawley
Senior Lecturer in Computing Sciences, University of East Anglia
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On over-fitting in model selection and subsequent selection bias in performance evaluation
GC Cawley, NLC Talbot
The Journal of Machine Learning Research 11, 2079-2107, 2010
Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers
GC Cawley, NLC Talbot
Pattern recognition 36 (11), 2585-2592, 2003
Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios
MR Haylock, GC Cawley, C Harpham, RL Wilby, CM Goodess
International Journal of Climatology: A Journal of the Royal Meteorological …, 2006
Extensive evaluation of neural network models for the prediction of NO2 and PM10 concentrations, compared with a deterministic modelling system and measurements in central Helsinki
J Kukkonen, L Partanen, A Karppinen, J Ruuskanen, H Junninen, ...
Atmospheric Environment 37 (32), 4539-4550, 2003
Fast exact leave-one-out cross-validation of sparse least-squares support vector machines
GC Cawley, NLC Talbot
Neural networks 17 (10), 1467-1475, 2004
Preventing Over-Fitting during Model Selection via Bayesian Regularisation of the Hyper-Parameters.
GC Cawley, NLC Talbot
Journal of Machine Learning Research 8 (4), 2007
Establishing glucose-and ABA-regulated transcription networks in Arabidopsis by microarray analysis and promoter classification using a Relevance Vector Machine
Y Li, KK Lee, S Walsh, C Smith, S Hadingham, K Sorefan, G Cawley, ...
Genome research 16 (3), 414-427, 2006
Gene selection in cancer classification using sparse logistic regression with Bayesian regularization
GC Cawley, NLC Talbot
Bioinformatics 22 (19), 2348-2355, 2006
Sparse multinomial logistic regression via bayesian l1 regularisation
G Cawley, N Talbot, M Girolami
Advances in neural information processing systems 19, 2006
Leave-one-out cross-validation based model selection criteria for weighted LS-SVMs
GC Cawley
The 2006 IEEE international joint conference on neural network proceedings …, 2006
Model selection: Beyond the Bayesian/frequentist divide
I Guyon, A Saffari, G Dror, G Cawley
Journal of Machine Learning Research 11 (Jan), 61-87, 2010
Nested cross-validation when selecting classifiers is overzealous for most practical applications
J Wainer, G Cawley
Expert Systems with Applications 182, 115222, 2021
A rigorous inter-comparison of ground-level ozone predictions
U Schlink, S Dorling, E Pelikan, G Nunnari, G Cawley, H Junninen, ...
Atmospheric Environment 37 (23), 3237-3253, 2003
Statistical models to assess the health effects and to forecast ground-level ozone
U Schlink, O Herbarth, M Richter, S Dorling, G Nunnari, G Cawley, ...
Environmental Modelling & Software 21 (4), 547-558, 2006
Design of the 2015 chalearn automl challenge
I Guyon, K Bennett, G Cawley, HJ Escalante, S Escalera, TK Ho, N Macià, ...
2015 International joint conference on neural networks (IJCNN), 1-8, 2015
Modelling SO2 concentration at a point with statistical approaches
G Nunnari, S Dorling, U Schlink, G Cawley, R Foxall, T Chatterton
Environmental Modelling & Software 19 (10), 887-905, 2004
Non-retrieval: blocking pornographic images
A Bosson, GC Cawley, Y Chan, R Harvey
International Conference on Image and Video Retrieval, 50-60, 2002
Results of the active learning challenge
I Guyon, GC Cawley, G Dror, V Lemaire
Active Learning and Experimental Design workshop In conjunction with AISTATS …, 2011
Improved sparse least-squares support vector machines
GC Cawley, NLC Talbot
Neurocomputing 48 (1-4), 1025-1031, 2002
MATLAB support vector machine toolbox
GC Cawley
University of East Anglia, School of Information Systems, Norwich, Norfolk …, 2000
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Artículos 1–20