Using FDE and DOE to Help Build Predictive Models for Spectral Data (2019-US-30MP-216)
Aug 27, 2019 12:45 PM
| Last Modified: Oct 21, 2019 9:56 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.