| A bias correction algorithm for the Gini variable importance measure in classification trees M Sandri, P Zuccolotto Journal of Computational and Graphical Statistics 17 (3), 611-628, 2008 | 208 | 2008 |
| Variable selection using random forests M Sandri, P Zuccolotto Data Analysis, Classification and the Forward Search: Proceedings of the …, 2006 | 146 | 2006 |
| Ripening transcriptomic program in red and white grapevine varieties correlates with berry skin anthocyanin accumulation M Massonnet, M Fasoli, GB Tornielli, M Altieri, M Sandri, P Zuccolotto, ... Plant Physiology 174 (4), 2376-2396, 2017 | 111 | 2017 |
| Sensory analysis in the food industry as a tool for marketing decisions M Iannario, M Manisera, D Piccolo, P Zuccolotto Advances in Data Analysis and classification 6, 303-321, 2012 | 103 | 2012 |
| A tail dependence-based dissimilarity measure for financial time series clustering G De Luca, P Zuccolotto Advances in data analysis and classification 5, 323-340, 2011 | 90 | 2011 |
| Big data analytics for modeling scoring probability in basketball: The effect of shooting under high-pressure conditions P Zuccolotto, M Manisera, M Sandri International journal of sports science & coaching 13 (4), 569-589, 2018 | 75 | 2018 |
| Grapevine field experiments reveal the contribution of genotype, the influence of environment and the effect of their interaction (G× E) on the berry transcriptome S Dal Santo, S Zenoni, M Sandri, G De Lorenzis, G Magris, E De Paoli, ... The Plant Journal 93 (6), 1143-1159, 2018 | 74 | 2018 |
| Pricing strategies for Italian red wine E Brentari, R Levaggi, P Zuccolotto Food Quality and Preference 22 (8), 725-732, 2011 | 67 | 2011 |
| Analysis and correction of bias in total decrease in node impurity measures for tree-based algorithms M Sandri, P Zuccolotto Statistics and Computing 20, 393-407, 2010 | 67 | 2010 |
| Modeling “don’t know” responses in rating scales M Manisera, P Zuccolotto Pattern Recognition Letters 45, 226-234, 2014 | 62 | 2014 |
| Discovering the drivers of football match outcomes with data mining M Carpita, M Sandri, A Simonetto, P Zuccolotto Quality Technology & Quantitative Management 12 (4), 561-577, 2015 | 58 | 2015 |
| Modeling rating data with nonlinear CUB models M Manisera, P Zuccolotto Computational Statistics & Data Analysis 78, 100-118, 2014 | 53 | 2014 |
| A novel tool for predicting extracapsular extension during graded partial nerve sparing in radical prostatectomy VR Patel, M Sandri, AAC Grasso, E De Lorenzis, F Palmisano, G Albo, ... BJU international 121 (3), 373-382, 2018 | 49 | 2018 |
| Basketball data science: With applications in R P Zuccolotto, M Manisera CRC Press, 2020 | 48 | 2020 |
| Regime-switching Pareto distributions for ACD models G De Luca, P Zuccolotto Computational Statistics & Data Analysis 51 (4), 2179-2191, 2006 | 43 | 2006 |
| Dynamic tail dependence clustering of financial time series G De Luca, P Zuccolotto Statistical papers 58, 641-657, 2017 | 42 | 2017 |
| Modelling the dynamic pattern of surface area in basketball and its effects on team performance R Metulini, M Manisera, P Zuccolotto Journal of Quantitative Analysis in Sports 14 (3), 117-130, 2018 | 37 | 2018 |
| Role revolution: towards a new meaning of positions in basketball F Bianchi, T Facchinetti, P Zuccolotto Electronic Journal of Applied Statistical Analysis 10 (3), 712-734, 2017 | 37 | 2017 |
| Is extraprostatic extension of cancer predictable? A review of predictive tools and an external validation based on a large and a single center cohort of prostate cancer patients B Rocco, MC Sighinolfi, M Sandri, A Eissa, A Elsherbiny, A Zoeir, ... Urology 129, 8-20, 2019 | 30 | 2019 |
| Football mining with R M Carpita, M Sandri, A Simonetto, P Zuccolotto Data mining applications with R, 397-434, 2014 | 26 | 2014 |
marica maniseraUniversity of Brescia, Italy在 eco.unibs.it 的电子邮件经过验证
