df_test = df_cluster.drop(items_train, axis=1) if method == 'HyObscure': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.HyObscure(df_train, grid_area_dict, area_grid_dict, cluster_num, grid_area_number, grid_list, area_reducibility, area_grid_rowcol_dict, area_grid_colrow_dict, method, grid_rowcol, grid_colrow, l_threshold, k_threshold, deltaX, pp) elif method == 'YGen': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.YGen(df_train, grid_area_dict, grid_area_number, cluster_num, grid_list, area_grid_dict, deltaX, area_reducibility, area_grid_rowcol_dict, area_grid_colrow_dict, method, grid_rowcol, grid_colrow, l_threshold, k_threshold, pp) elif method == 'XObf': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.XObf(df_train, cluster_num, grid_area_number, grid_list, grid_area_dict, area_grid_dict, deltaX, pp, method) elif method == 'PrivCheck': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.PrivCheck(df_train, cluster_num, grid_list, grid_area_dict, grid_area_number, area_grid_dict, deltaX, pp) elif method == 'DP': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.differential_privacy(df_train, grid_area_dict, grid_area_number, beta) elif method == 'Frapp': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Frapp(df_train, grid_area_dict, gamma) elif method == 'Random': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Random(df_train, grid_area_dict, p_rand) elif method == 'Sim': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Similarity(df_train, grid_area_dict, pp) else: print('Method error. Check method setting.') break df_test = funcs.update_grid_group(df_test, grid_area_dict) rec_oris = [] rec_obfs = [] acc_oris_rf = []
X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.YGen( df_train, df_test, df_test_rec_items, df_item_age_uid, age_group_number, cluster_num, deltaX, age_list, age_group_dict, group_age_dict, k_threshold, l_threshold, pp) elif method == 'XObf': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.XObf( df_train, df_test, age_group_number, cluster_num, deltaX, age_list, group_age_dict, pp) elif method == 'PrivCheck': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.PrivCheck( df_train, df_test, df_test_rec_items, age_group_number, cluster_num, deltaX, age_list, age_group_dict, group_age_dict, pp) elif method == 'DP': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.differential_privacy( df_train, df_test, df_test_rec_items, age_group_dict, beta) elif method == 'Frapp': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Frapp( df_train, df_test, df_test_rec_items, age_group_dict, gamma, pp) elif method == 'Random': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Random( df_train, df_test, df_test_rec_items, age_group_dict, p_rand, pp) elif method == 'Sim': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Similarity( df_train, df_test, df_test_rec_items, age_group_dict, pp) else: print('Method error. Check method setting.') break
elif method == 'YGen': X_obf_dict, X_ori = obfuscations.YGen( df_train, age_group_number, cluster_num, age_list, age_group_dict, group_age_dict, df_item_age_uid, deltaX, k_threshold, l_threshold, pp) elif method == 'XObf': X_obf_dict, X_ori = obfuscations.XObf(deltaX, cluster_num, age_group_number, age_list, group_age_dict, df_train, pp) elif method == 'PrivCheck': X_obf_dict, X_ori = obfuscations.PrivCheck( deltaX, cluster_num, age_group_number, df_cluster, df_train, age_list, age_group_dict, group_age_dict, pp) elif method == 'DP': X_obf_dict, X_ori = obfuscations.differential_privacy( df_train, age_group_dict, beta) elif method == 'Frapp': X_obf_dict, X_ori = obfuscations.Frapp(df_train, df_test, age_group_dict, gamma) elif method == 'Random': X_obf_dict, X_ori = obfuscations.Random( df_train, age_group_dict, p_rand) elif method == 'Sim': X_obf_dict, X_ori = obfuscations.Similarity( df_train, age_group_dict, pp) else: print('Method error. Check method setting.') break rec_oris = [] rec_obfs = []
grid_area_number, grid_list, area_grid_dict, grid_area_dict, l_threshold, k_threshold, area_reducibility, area_grid_rowcol_dict, area_grid_colrow_dict, grid_rowcol, grid_colrow, deltaX, pp, method) elif method == 'XObf': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.XObf( df_train, df_test, deltaX, cluster_num, grid_area_number, grid_list, area_grid_dict, pp, method) elif method == 'PrivCheck': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.PrivCheck( df_train, df_test, df_test_rec_items, grid_area_dict, area_grid_dict, grid_list, cluster_num, grid_area_number, deltaX, pp) elif method == 'DP': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.differential_privacy( df_train, df_test, grid_area_dict, df_test_rec_items, beta) elif method == 'Frapp': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Frapp( df_train, df_test, grid_area_dict, df_test_rec_items, gamma, pp) elif method == 'Random': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Random( df_train, df_test, grid_area_dict, df_test_rec_items, p_rand, pp) elif method == 'Sim': X_obf_dict, X_ori, model_rf, model_xgb = obfuscations.Similarity( df_train, df_test, df_test_rec_items, grid_area_dict, pp) else: print('Method error. Check method setting.') break