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Herrera, L. J., Rubio, G., Pomares, H., Paechter, B., Guillén, A., & Rojas, I. (2009). Strengthening the Forward Variable Selection Stopping Criterion. In Artificial Neural Networks – ICANN 2009; Lecture Notes in Computer Science, 215-224. BMC. https://doi.org/10.1007/978-3-642-04277-5_22
Given any modeling problem, variable selection is a preprocess step that selects the most relevant variables with respect to the output variable. Forward selection is the most...