Machine learning

Regresija Lasso

Regresija Lasso, koju je Robert Tibshirani uveo 1996. godine, jest metoda linearne regresije koja dodaje L1 kaznu na gubitak kako bi smanjila koeficijente i istodobno provela odabir varijabli, proizvodeći rijedak model. Tjerajući neke koeficijente točno na nulu, zadržava samo prediktore koji su važni.

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Izvori

  1. Tibshirani, R. (1996). Regression Shrinkage and Selection via the Lasso. Journal of the Royal Statistical Society: Series B, 58(1), 267–288. DOI: 10.1111/j.2517-6161.1996.tb02080.x

Kako citirati ovu stranicu

ScholarGate. (2026, June 1). Least Absolute Shrinkage and Selection Operator (LASSO). ScholarGate. https://scholargate.app/hr/machine-learning/lasso-regression

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Citirana u

ScholarGateLasso Regression (Least Absolute Shrinkage and Selection Operator (LASSO)). Preuzeto 2026-06-15 s https://scholargate.app/hr/machine-learning/lasso-regression · Skup podataka: https://doi.org/10.5281/zenodo.20539026