Título: Random Machines: a new bagged-weighted support vector model

Palestrante :Anderson Luiz Ara Souza (UFBA)
Data: 25/08/2021
Horário: 15:30h
Local: Transmissão online

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Resumo: Improvement of statistical learning models to increase efficiency in solving classification or regression problems is a goal pursued by the scientific community. Particularly, the support vector machine model has become one of the most successful algorithms for this task. Despite the strong predictive capacity from the support vector approach, its performance relies on the selection of hyperparameters of the model, such as the kernel function that will be used. The traditional procedures to decide which kernel function will be used are computationally expensive. In this presentation, we proposed a novel framework to deal with the kernel function selection called Random Machines. The results display an improvement in the predictive capacity as well as reduced computational time.

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