Publications

Andrews curves Applied Machine Learning Bagging Boosting Business intelligence Chomsky normal form Class-imbalanced problems Classifier ensembles Cocke-Younger-Kasami algorithm Computer Science teaching Data analysis Data Mining Data visualization Decision trees Disturbing neighbors End of studies project Ensemble methods Ensembles Exploratory data analysis Exploratory projection pursuit Finite automata Grammars Imbalanced data Instance selection Linear projections LL parsing Machine learning Multi-label classification Neural networks Parsing algorithms Random forest Random oracles Regression Regression ensembles Regression trees Regular expressions Rotation forest Self organizing maps Support vector machines surface roughness

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2013

Rodríguez, Juan José; Díez-Pastor, José Francisco; García-Osorio, César

Random Oracle Ensembles for Imbalanced Data Inproceedings

In: Zhou, Zhi-Hua; Roli, Fabio; Kittler, Josef (Ed.): 11th International Workshop on Multiple Classifier Systems, MCS 2013, pp. 247-258, Nanjing, China, 2013, ISBN: 978-3-642-38066-2.

Links | BibTeX | Tags: Class-imbalanced problems, Data Mining, Ensemble methods, Random oracles

2011

Pardo, Carlos; Rodríguez, Juan José; Díez-Pastor, José Francisco; García-Osorio, César

Random Oracles for Regression Ensembles Book Chapter

In: Okun, Oleg; Valentini, Giorgio; Re, Matteo (Ed.): Ensembles in Machine Learning Applications, 373 , pp. 181-199, Springer, 2011, ISBN: 978-3-642-22909-1.

Links | BibTeX | Tags: Data Mining, Random oracles, Regression ensembles

Pardo, Carlos; Rodríguez, Juan José; Díez-Pastor, José Francisco; García-Osorio, César

Random Oracles for Regression Ensembles Book Chapter

In: Ensembles in Machine Learning Applications, 373 , pp. 181-199, 2011, ISSN: 1860-949X.

Links | BibTeX | Tags: Data Mining, Random oracles, Regression ensembles

2010

Pardo, Carlos; Rodríguez, Juan José; Díez-Pastor, José Francisco; García-Osorio, César

Random Oracles for Regression Ensembles Inproceedings

In: Workshop on Supervised and Unsupervised Ensemble Methods and their Applications, SUEMA 2010, pp. 85-96, 2010.

BibTeX | Tags: Data Mining, Random oracles, Regression ensembles