Bachelor in Statistics from the USP (Universidade de São Paulo) em 2020 and Master in Statistics also from the USP (2021-2023). He is currently a Ph.D. candidate in Statistics at the USP. He is interested in the area of regression models, working mainly on the generalized additive models. (Source: Lattes Curriculum)
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In this work, we will study the theoretical methodology of support vector regression (SVR), aimed at analyzing the data sets with high dimension. Our objective is to compare the performance of this technique with conventional parametric techniques. The parametric methods to be compared are: Ridge regression and Lasso. These parametric methods are most commonly used in high-dimensional pro…
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