def main(): #import bogota.data options = DEFAULT_OPTIONS print 'Getting Data' #data = get_data(bogota.data.cn_all9, 0, normalise=50., seed=101) data = GameData('./all9.csv', 50.) train_data, test_data = data.train_test(0, seed=101) perf, par = train( options, [train_data.datalist(), test_data.datalist()], False) for k, v in par.iteritems(): print k print v
def fold_function(k): # k is the fold index data = GameData('./all9.csv', 50.) train_data, test_data = data.train_test(k, seed=seed) options['fold'] = k llk, best_par = train(options, [train_data.datalist(), test_data.datalist()], False) print "LLK: ", llk for kk, vv in best_par.items(): temp = vv.tolist() del best_par[kk] best_par[kk] = temp log_fold(best_loss_filename, llk, k, options.get('model_seed', -99)) with open(par_file % k, 'w') as f: json.dump(best_par, f)