Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach

@inproceedings{Prudncio2011SelectingML,
  title={Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach},
  author={Ricardo B. C. Prud{\^e}ncio and Marc{\'i}lio Carlos Pereira de Souto and Teresa Bernarda Ludermir},
  booktitle={Meta-Learning in Computational Intelligence},
  year={2011}
}
In this work, we present the use of Ranking Meta-Learning approaches to ranking and selecting algorithms for problems of time series forecasting and clustering of gene expression data. Given a problem (forecasting or clustering), the Meta-Learning approach provides a ranking of the candidate algorithms, according to the characteristics of the problem’s dataset. The best ranked algorithm can be returned as the selected one. In order to evaluate the Ranking Meta-Learning proposal, prototypes were… CONTINUE READING
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