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Ranking Learning Algorithms: Using IBL and Meta-Learning on Accuracy and Time Results.

, , and . Mach. Learn., 50 (3): 251-277 (2003)

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AToMRS: A Tool to Monitor Recommender Systems., , and . KDIR, page 133-140. SciTePress, (2016)A hybrid meta-learning architecture for multi-objective optimization of SVM parameters., , , and . Neurocomputing, (2014)A comprehensive comparison of ML algorithms for gene expression data classification., , and . IJCNN, page 1-8. IEEE, (2010)MetaStream: A meta-learning based method for periodic algorithm selection in time-changing data., , , and . Neurocomputing, (2014)Arbitrated Ensemble for Solar Radiation Forecasting., , and . IWANN (1), volume 10305 of Lecture Notes in Computer Science, page 720-732. Springer, (2017)A Comparison of Ranking Methods for Classification Algorithm Selection., and . ECML, volume 1810 of Lecture Notes in Computer Science, page 63-74. Springer, (2000)Learning from the News: Predicting Entity Popularity on Twitter., and . IDA, volume 9897 of Lecture Notes in Computer Science, page 171-182. (2016)TimeMachine: Entity-Centric Search and Visualization of News Archives., , , and . ECIR, volume 9626 of Lecture Notes in Computer Science, page 845-848. Springer, (2016)Active selection of training instances for a random forest meta-learner., , , and . IJCNN, page 1-7. IEEE, (2013)Monitoring the Quality of Meta-data in Web Portals Using Statistics, Visualization and Data Mining., , and . EPIA, volume 3808 of Lecture Notes in Computer Science, page 371-382. Springer, (2005)