Sorting variables by using informative vectors as a strategy for feature selection in multivariate regression

By R. Teófilo, João Paulo Ataide Martins, Márcia M. C. Ferreira. 2009

208 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/3e717a23d9b36fa57591c33ea9fea0ef0b621528

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. A. Gomes
2. Edvan Cirino da Silva
3. Germano Véras
4. Roberto Kawakami Harrop Galvão
5. Mário César Ugulino de Araújo

In Industrial and Manufacturing Engineering

1. Edvan Cirino da Silva
2. A. Gomes
3. Roberto Kawakami Harrop Galvão
4. Mário César Ugulino de Araújo

Citations in the corpus

• The successive projections algorithm for interval selection in PLS (2013, methodology): “This investigation is in line with previous works that have reported improvements in PLS through the use of variable selection strategies, such as Genetic Algorithms (GA-PLS) [25], Backward Variable Selection for PLS [26], Iterative Predictor Weighting PLS [27], Elimination of Uninformative Variable”