Python Hyperspectral Analysis Tool (PyHAT) Regression Example

This figure compares the results of two regression models to predict the abundance of CaO in geologic standards based on their laser induced breakdown spectroscopy (LIBS) spectra using PyHAT. The horizontal axis is the independently measured CaO abundance, the vertical axis is the abundance predicted by the models. A perfect model would have results that plot on the black "one-to-one" line. The spectra use to train and test the models were preprocessed using PyHAT and the models were optimized using PyHAT's cross validation capabilities.

This figure is one of a series of figures used to demonstrate some of the capabilities of the PyHAT software.