| La minería de datos, entre la estadística y la inteligencia artificial T Aluja Banet Institut d'Estadística de Catalunya, 2001 | 157 | 2001 |
| Aprender de los Datos: El Análsis de Componentes Principales AM Tomàs Aluja Banet Ediciones Universitarias de Barcelona, 1999 | 150* | 1999 |
| Toward the definition of a structural equation model of patent value: PLS path modelling with formative constructs A Martinez-Ruiz, T Aluja-Banet REVSTAT-Statistical Journal 7 (3), 265–290-265–290, 2009 | 84 | 2009 |
| On the predictive power of meta-features in OpenML B Bilalli, A Abelló, T Aluja-Banet International Journal of Applied Mathematics and Computer Science 27 (4 …, 2017 | 77 | 2017 |
| Measuring Motivation from the Virtual Learning Environment in Secondary Education MRSIV Tomas Aluja-Banet Journal of Computational Science, 2017 | 73* | 2017 |
| Intelligent assistance for data pre-processing B Bilalli, A Abelló, T Aluja-Banet, R Wrembel Computer Standards & Interfaces 57, 101-109, 2018 | 61 | 2018 |
| Analyse en composantes principales (avec illustrations SPAD) A Morineau, T Aluja-Banet CISIA-CERESTA, 1998 | 54 | 1998 |
| Competencias profesionales del grado en ingeniería informática F Sánchez, MR Sancho, P Botella, J García, T Aluja, J Navarro, ... Actas de las XIV Jornadas de Enseñanza Universitaria de Informàtica, JENUI …, 2008 | 45 | 2008 |
| Knowledge discovery with clustering based on rules. Interpreting results K Gibert, T Aluja, U Cortés Principles of Data Mining and Knowledge Discovery: Second European Symposium …, 1998 | 39 | 1998 |
| Towards Intelligent Data Analysis: The Metadata Challenge. B Bilalli, A Abelló, T Aluja-Banet, R Wrembel IoTBD, 331-338, 2016 | 37 | 2016 |
| PRESISTANT: Learning based assistant for data pre-processing B Bilalli, A Abelló, T Aluja-Banet, R Wrembel Data & Knowledge Engineering 123, 101727, 2019 | 36 | 2019 |
| Work climate drivers and employee heterogeneity G Lamberti, T Aluja Banet, J Rialp Criado The International Journal of Human Resource Management 33 (3), 472-504, 2022 | 35 | 2022 |
| The Pathmox approach for PLS path modeling segmentation G Lamberti, TB Aluja, G Sanchez Applied Stochastic Models in Business and Industry 32 (4), 453-468, 2016 | 35 | 2016 |
| PATHMOX approach: Segmentation Trees in Partial Least Squares path Modeling GS Trujillo Universitat Politecnica de Catalunya - Barcelona Tech, 2009 | 35 | 2009 |
| GRAFT, a complete system for data fusion T Aluja-Banet, J Daunis-i-Estadella, D Pellicer Computational statistics & Data analysis 52 (2), 635-649, 2007 | 35 | 2007 |
| Optimal representation of supplementary variables in biplots from principal component analysis and correspondence analysis J Graffelman, T Aluja‐Banet Biometrical Journal: Journal of Mathematical Methods in Biosciences 45 (4 …, 2003 | 34 | 2003 |
| Pathmox: a PLS-PM segmentation algorithm G Sánchez, T Aluja Proceedings of KNEMO 69, 2006 | 33 | 2006 |
| Stability and scalability in decision trees T Aluja-Banet, E Nafria Computational Statistics 18 (3), 505-520, 2003 | 28 | 2003 |
| Automated data pre-processing via meta-learning B Bilalli, A Abelló, T Aluja-Banet, R Wrembel International Conference on Model and Data Engineering, 194-208, 2016 | 26 | 2016 |
| Local and partial principal component analysis (PCA) and correspondence analysis (CA) TA Banet, L Lebart Compstat 1984: Proceedings in Computational Statistics, 113-118, 1984 | 26 | 1984 |
