The electron-boson spectral density (or glue) function can be obtained from measured optical scattering rate by solving a generalized Allen formula, which relates the two quantities with an integral equation and is an inversion problem. Thus far, numerical approaches, such as the maximum entropy method (MEM) and the least squares fitting method, have been applied for solving the generalized Allen formula. Here, we developed a new method to obtain the glue functions from the optical scattering rate using a machine learning approach (MLA). We found that the MLA is more robust against random noise compared with the MEM. We applied the new developed MLA to experimentally measured optical scattering rates and obtained reliable glue functions in terms of their shapes including the amplitudes. We expect that the MLA can be a useful and rapid method for solving other inversion problems, which may contain random noise.
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