Before revision: The inverse Potts problem to infer the Boltzmann distribution for homologous protein sequences from their single-site and pairwise  frequencies recently attracts a great deal of attention due to its capacity to accurately predict residue-residue contacts in a 3D protein complex. A Boltzmann machine for the accurate estimation of the field and coupling interactions, which is required for other studies in protein evolution and folding, is studied about learning methods , regularization models and a tuning method of regularization parameters in order to infer the interactions with reasonable characteristics . Using L_2 regularization for fields, group L_1 for couplings is shown to be very effective for parse couplings in comparison with L_2 and with L_1.
After revision: The inverse Potts problem to infer the Boltzmann distribution for homologous protein sequences from their single-site and pairwise frequencies recently attracts a great deal of attention in the studies of protein structure and evolution. We study regularization and learning methods and folding, is studied about learning methods , regularization models and a tuning method of regularization parameters in order to infer the interactions with reasonable characteristics . Using L_2 regularization for fields, group L_1 for couplings is shown to be very effective for parse couplings in comparison with L_2 and with L_1.