| Variable selection for model-based clustering AE Raftery, N Dean Journal of the American Statistical Association 101 (473), 168-178, 2006 | 546 | 2006 |
| Latent class analysis variable selection N Dean, AE Raftery Annals of the Institute of Statistical Mathematics 62 (1), 11, 2010 | 133 | 2010 |
| Using unlabelled data to update classification rules with applications in food authenticity studies N Dean, TB Murphy, G Downey Journal of the Royal Statistical Society: Series C (Applied Statistics) 55 …, 2006 | 110 | 2006 |
| Normal uniform mixture differential gene expression detection for cDNA microarrays N Dean, AE Raftery BMC bioinformatics 6 (1), 173, 2005 | 76 | 2005 |
| Q-learning: Flexible learning about useful utilities EEM Moodie, N Dean, YR Sun Statistics in Biosciences 6 (2), 223-243, 2014 | 74 | 2014 |
| Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications TB Murphy, N Dean, AE Raftery The annals of applied statistics 4 (1), 396, 2010 | 69 | 2010 |
| A Comparison of Student Skill Knowledge Estimates. E Ayers, R Nugent, N Dean International Working Group on Educational Data Mining, 2009 | 62 | 2009 |
| Identifying clusters in Bayesian disease mapping C Anderson, D Lee, N Dean Biostatistics 15 (3), 457-469, 2014 | 54 | 2014 |
| Skill set profile clustering based on student capability vectors computed from online tutoring data E Ayers, R Nugent, N Dean | 38 | 2008 |
| Skill set profile clustering: the empty K-means algorithm with automatic specification of starting cluster centers R Nugent, N Dean, E Ayers Educational data mining 2010, 2010 | 30 | 2010 |
| A Survey of Popular R Packages for Cluster Analysis A Flynt, N Dean Journal of Educational and Behavioral Statistics 41 (2), 205-225, 2016 | 19 | 2016 |
| Conditional Subspace Clustering of Skill Mastery: Identifying Skills that Separate Students. R Nugent, E Ayers, N Dean International Working Group on Educational Data Mining, 2009 | 17 | 2009 |
| Frontiers in residential segregation: Understanding neighbourhood boundaries and their impacts N Dean, G Dong, A Piekut, G Pryce Tijdschrift voor economische en sociale geografie 110 (3), 271-288, 2019 | 14 | 2019 |
| Bayesian cluster detection via adjacency modelling C Anderson, D Lee, N Dean Spatial and spatio-temporal epidemiology 16, 11-20, 2016 | 13 | 2016 |
| Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra A Martyna, G Zadora, T Neocleous, A Michalska, N Dean Analytica Chimica Acta 931, 34-46, 2016 | 9 | 2016 |
| Spatial clustering of average risks and risk trends in Bayesian disease mapping C Anderson, D Lee, N Dean Biometrical Journal 59 (1), 41-56, 2017 | 8 | 2017 |
| Clustering student skill set profiles in a unit hypercube using mixtures of multivariate betas N Dean, R Nugent Advances in Data Analysis and Classification 7 (3), 339-357, 2013 | 7 | 2013 |
| clustvarsel: Variable selection for model-based clustering N Dean, AE Raftery, L Scrucca R package version 1, 2009 | 6 | 2009 |
| The clustvarsel package N Dean, AE Raftery R package version 0.2-4, 2006 | 6 | 2006 |
| Benchmarking in cluster analysis: A white paper I Van Mechelen, AL Boulesteix, R Dangl, N Dean, I Guyon, C Hennig, ... arXiv preprint arXiv:1809.10496, 2018 | 5 | 2018 |
