| Increasing crop diversity mitigates weather variations and improves yield stability ACM Gaudin, TN Tolhurst, AP Ker, K Janovicek, C Tortora, RC Martin, ... PloS one 10 (2), e0113261, 2015 | 467 | 2015 |
| A mixture of generalized hyperbolic factor analyzers C Tortora, PD McNicholas, RP Browne Advances in Data Analysis and Classification 10 (4), 423-440, 2016 | 64 | 2016 |
| A mixture of coalesced generalized hyperbolic distributions C Tortora, BC Franczak, RP Browne, PD McNicholas Journal of Classification 36, 26-57, 2019 | 38 | 2019 |
| MixGHD: model based clustering, classification and discriminant analysis using the mixture of generalized hyperbolic distributions C Tortora, RP Browne, BC Franczak, PD McNicholas R package version 1, 2015 | 35 | 2015 |
| Categorizing three active cyclist typologies by exploring patterns on a multitude of GPS crowdsourced data attributes. C Poliziani, F Rupi, F Mbuga, J Schweizer, C Tortora Research in Transportation Business & Management 40, 100572, 2021 | 28 | 2021 |
| Unsupervised learning via mixtures of skewed distributions with hypercube contours BC Franczak, C Tortora, RP Browne, PD McNicholas Pattern Recognition Letters 58, 69-76, 2015 | 28 | 2015 |
| Multiple scaled contaminated normal distribution and its application in clustering A Punzo, C Tortora Statistical Modelling 21 (4), 332-358, 2021 | 24 | 2021 |
| Benchmarking in cluster analysis: a study on spectral clustering, DBSCAN, and K-Means N Murugesan, I Cho, C Tortora Conference of the International Federation of Classification Societies, 175-185, 2019 | 22 | 2019 |
| Factor probabilistic distance clustering (FPDC): a new clustering method C Tortora, MG Summa, M Marino, F Palumbo Advances in Data Analysis and Classification 10, 441-464, 2016 | 18 | 2016 |
| Model-based clustering, classification, and discriminant analysis using the generalized hyperbolic distribution: MixGHD R package C Tortora, RP Browne, A ElSherbiny, BC Franczak, PD McNicholas Journal of Statistical Software 98, 1-24, 2021 | 17 | 2021 |
| Clustering mixed-type data using a probabilistic distance algorithm C Tortora, F Palumbo Applied Soft Computing 130, 109704, 2022 | 16 | 2022 |
| A mixture of coalesced generalized hyperbolic distributions C Tortora, BC Franczak, RP Browne, PD McNicholas arXiv preprint arXiv:1403.2332, 2014 | 15 | 2014 |
| Factor pd-clustering C Tortora, MG Summa, F Palumbo Algorithms from and for Nature and Life: Classification and Data Analysis …, 2013 | 15* | 2013 |
| A Probabilistic Distance Clustering Algorithm Using Gaussian and Student-t Multivariate Density Distributions C Tortora, PD McNicholas, F Palumbo SN Computer Science 1 (2), 65, 2020 | 12 | 2020 |
| Assembly rules vary seasonally in stable phytoplankton associations of the Gulf of Naples (Mediterranean Sea) A Zingone, C Tortora, D D′ Alelio, F Margiotta, D Sarno Marine Ecology 44 (3), e12730, 2023 | 11 | 2023 |
| Model-based clustering and outlier detection with missing data H Tong, C Tortora Advances in Data Analysis and Classification 16 (1), 5-30, 2022 | 10 | 2022 |
| Spectral clustering of mixed-type data F Mbuga, C Tortora Stats 5 (1), 1-11, 2021 | 10 | 2021 |
| Beyond skill: students' dispositions towards math W Maciejewski, C Tortora, J Bragelman Journal of Developmental Education, 18-25, 2021 | 10 | 2021 |
| Crime and harassment on public transportation: A survey of SJSU students set in international context AW Agrawal, A Loukaitou-Sideris, C Tortora, Y Hu | 10 | 2020 |
| Clustering mixed-type data: a benchmark study on KAMILA and k-prototypes J Jimeno, M Roy, C Tortora Data Analysis and Rationality in a Complex World 16, 83-91, 2021 | 9 | 2021 |
