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Algorithm recommendation and performance prediction using meta-learning

Palumbo, Guilherme; Carneiro, Davide Rua; Guimares, Miguel; Alves, Victor; Novais, Paulo

In the last years, the number of machine learning algorithms and their parameters has increased significantly. On the one hand, this increases the chances of finding better models. On the other hand, it increases the complexity of the task of training a model, as the search space expands significantly. As the size of datasets also grows, traditional approaches based on extensive search start to become prohibiti...


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