5 papers
Capturing waste collection planning expert knowledge in a fitness function through preference learning
Laura Fernández DÃaz, Miriam Fernández DÃaz, José Ramón Quevedo +1
This paper copes with the COGERSA waste collection process. Up to now, experts have been manually designed the process using a trial and error mechanism. This process is not global…
Improving importance estimation in covariate shift for providing accurate prediction error
Laura Fdez-DÃaz, Sara González Tomillo, Elena Montañés +1
In traditional Machine Learning, the algorithms predictions are based on the assumption that the data follows the same distribution in both the training and the test datasets. Howe…
Regularized boosting with an increasing coefficient magnitude stop criterion as meta-learner in hyperparameter optimization stacking ensemble
Laura Fdez-DÃaz, José Ramón Quevedo, Elena Montañés
In Hyperparameter Optimization (HPO), only the hyperparameter configuration with the best performance is chosen after performing several trials, then, discarding the effort of trai…
Direct side information learning for zero-shot regression
Miriam Fdez-DÃaz, Elena Montañés, José Ramón Quevedo
Zero-shot learning provides models for targets for which instances are not available, commonly called unobserved targets. The availability of target side information becomes crucia…
Target inductive methods for zero-shot regression
Miriam Fdez-DÃaz, José Ramón Quevedo, Elena Montañés
This research arises from the need to predict the amount of air pollutants in meteorological stations. Air pollution depends on the location of the stations (weather conditions and…