| Software development effort estimation using fuzzy logic: a case study CL Martín, JL Pasquier, CM Yanez, AG Tornes Sixth Mexican International Conference on Computer Science (ENC'05), 113-120, 2005 | 82 | 2005 |
| Predictive accuracy comparison between neural networks and statistical regression for development effort of software projects C López-Martín Applied Soft Computing 27, 434-449, 2015 | 81 | 2015 |
| Support vector regression for predicting software enhancement effort A García-Floriano, C López-Martín, C Yáñez-Márquez, A Abran Information and Software Technology 97, 99-109, 2018 | 70 | 2018 |
| Software development effort prediction of industrial projects applying a general regression neural network C Lopez-Martin, C Isaza, A Chavoya Empirical Software Engineering 17, 738-756, 2012 | 64 | 2012 |
| Neural networks for predicting the duration of new software projects C López-Martín, A Abran Journal of Systems and Software 101, 127-135, 2015 | 59 | 2015 |
| A fuzzy logic model for predicting the development effort of short scale programs based upon two independent variables C Lopez-Martin Applied Soft Computing 11 (1), 724-732, 2011 | 53 | 2011 |
| Predictive accuracy comparison of fuzzy models for software development effort of small programs C López-Martín, C Yáñez-Márquez, A Gutiérrez-Tornés Journal of Systems and Software 81 (6), 949-960, 2008 | 53 | 2008 |
| Neural networks for predicting student performance in online education RLU Cazarez, CL Martin IEEE Latin America Transactions 16 (7), 2053-2060, 2018 | 37 | 2018 |
| Applying a feedforward neural network for predicting software development effort of short-scale projects I Kalichanin-Balich, C Lopez-Martin 2010 Eighth ACIS International Conference on Software Engineering Research …, 2010 | 35 | 2010 |
| A comparative study of two fuzzy logic models for software development effort estimation N Garcia-Diaz, C Lopez-Martin, A Chavoya Procedia Technology 7, 305-314, 2013 | 34 | 2013 |
| Applying a general regression neural network for predicting development effort of short-scale programs C Lopez-Martin Neural Computing and Applications 20, 389-401, 2011 | 23 | 2011 |
| Machine learning techniques for software testing effort prediction C López-Martín Software Quality Journal 30 (1), 65-100, 2022 | 19 | 2022 |
| Transformed k-nearest neighborhood output distance minimization for predicting the defect density of software projects C López-Martín, Y Villuendas-Rey, M Azzeh, AB Nassif, S Banitaan Journal of Systems and Software 167, 110592, 2020 | 19 | 2020 |
| Applying expert judgment to improve an individual's ability to predict software development effort C Lopez-Martin, A Abran International Journal of Software Engineering and Knowledge Engineering 22 …, 2012 | 18 | 2012 |
| Support vector regression for predicting the enhancement duration of software projects C Lopez-Martin, S Banitaan, A Garcia-Floriano, C Yanez-Marquez 2017 16th IEEE International Conference on Machine Learning and Applications …, 2017 | 16 | 2017 |
| Use of a feedforward neural network for predicting the development duration of software projects C López-Martín, A Chavoya, ME Meda-Campaña 2013 12th International Conference on Machine Learning and Applications 2 …, 2013 | 16 | 2013 |
| Application of Gamma classifier to development effort prediction of software projects C López-Martın, I Lopez-Yanez, C Yanez-Marquez Appl. Math 6 (3), 411-418, 2012 | 16 | 2012 |
| Stochastic gradient boosting for predicting the maintenance effort of software‐intensive systems S Cerón-Figueroa, C López-Martín, C Yáñez-Márquez IET Software 14 (2), 82-87, 2020 | 14 | 2020 |
| Prediction of online students performance by means of genetic programming RL Ulloa-Cazarez, C López-Martín, A Abran, C Yáñez-Márquez Applied Artificial Intelligence 32 (9-10), 858-881, 2018 | 14 | 2018 |
| A machine learning technique for predicting the productivity of practitioners from individually developed software projects C Lopez-Martin, A Chavoya, ME Meda-Campaña 15th IEEE/ACIS International Conference on Software Engineering, Artificial …, 2014 | 14 | 2014 |
