Data preprocessing is a crucial stage in the performance of linear regression models, where data quality including the handling of missing values, outlier detection, normalization, and variable encoding directly influences the predictive capability of machine learning algorithms. This systematic review, conducted under...
Jaime David Camacho Castillo, Mauricio Alexander Álvarez Ortega, Iván Alejandro Daqui Cabezas et al.· Tesla Revista Científica· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.