A Comparison of Sparse Partial Least Squares and Elastic Net in Wavelength Selection on NIR Spectroscopy Data

Figure 6

The coefficient paths of predictor matrix “m5spec” with four responses from corn data set. The left and right four panels are generated by Enet and SPLS, respectively. All the panels show that the coefficients paths are segmentally zero-valued or nonzero-valued, so two methods select successive wavelength intervals as key variables.