Using FDE and DOE to Help Build Predictive Models for Spectral Data (2020-EU-30MP-410)
Jan 30, 2020 7:52 AM
| Last Modified: Aug 4, 2020 9:37 AM
Bill Worley, JMP Senior Global Enablement Engineer, SAS
In the recent past Partial Least Squares (PLS) has been used to build predictive models for spectral data. A newer approach using Functional Data Explorer (FDE) and Covariate Design of Experiments (DOE) will be shown that will allow for fewer spectra to be used in the development of a good predictive model. This method uses one-fourth to one-third of the data that would otherwise be used to build a predictive model based on spectral data.