ind = 0 for a in alpha: metrics = np.zeros([model_no, 8]) k = 1 for i in columns: sheets[ind].write(0, k, i) k += 1 for mod in range(model_no): sheets[ind].write(mod + 1, 0, 'model_{}'.format(mod)) for train_index, test_index in skf.split(atribute, output): lst = [ models.Fair_PR(sensitive=prot, class_attr='labels', eta=eta[ind]), models.Fair_meta(sensitive=prot, tau=eta[ind]), models.Fair_DI_NN(sensitive=prot, inp_size=inp, num_layers_y=3, step_y=1.5, repair_level=eta[ind]), models.Fair_DI_RF(sensitive=prot, repair_level=eta[ind]), models.Fair_rew_NN(un_gr, pr_gr, inp_size=inp, num_layers_y=3, step_y=1.5), models.Fair_rew_RF(un_gr, pr_gr), models.FAD_class(input_size=inp, num_layers_z=3,
sheets = [wb.add_sheet('{}'.format(i)) for i in alpha] ind = 0 for a in alpha: metrics = np.zeros([model_no, 8]) k = 1 for i in columns: sheets[ind].write(0, k, i) k += 1 for mod in range(model_no): sheets[ind].write(mod + 1, 0, 'model_{}'.format(mod)) lst = [ models.Fair_PR(sensitive=prot, class_attr='readmitBIN', eta=eta[ind]), models.Fair_meta(sensitive=prot, tau=eta[ind]), models.Fair_DI_NN(sensitive=prot, inp_size=inp, num_layers_y=3, step_y=1.5, repair_level=eta[ind]), models.Fair_DI_RF(sensitive=prot, repair_level=eta[ind]), models.Fair_rew_NN(un_gr, pr_gr, inp_size=inp, num_layers_y=3, step_y=1.5), models.Fair_rew_RF(un_gr, pr_gr), models.FAD_class(input_size=inp, num_layers_z=3,