Multifrequency atomic force microscopy (AFM) enhances resolving power, provides extra contrast channels, and is equipped with a formalism to quantify material properties pixel by pixel. On the other hand, multifrequency AFM lacks the ability to extract and examine the profile to validate a given force model while scanning. We propose exploiting data-driven algorithms, i.e., machine learning packages, ...