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Using FDE and DOE to Help Build Predictive Models for Spectral Data (2019-US-30MP-216)

Level: Intermediate


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.