Surface roughness prediction using kernel locality preserving projection and Bayesian linear regression

•A new two-stage feature-fusion method by combining PCA and KLPP is presented.•A unique approach for determining the model parameters of KLPP is presented.•KLPP is comprehensively analyzed under three weighting methods.•KLPP helps to improve the prediction accuracy and compress the CI of Standard_SBLR.•Under the support of KLPP, Standard_SBLR shows superior predictive performance.