Abstract
This paper concerns the effect of the subsampling ratio on the subagging approach for multiple linear regression with variable selection by the successive projections algorithm. Investigations involving simulated data, as well as near-infrared spectrometric determination of moisture and protein in wheat and distillation temperatures (T10 and T90), specific mass and sulphur in diesel, are presented. In terms of prediction ability and sensitivity to noise, the best results were obtained for subsampling ratios around 40%.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
