from encoding import adult from encoding import hamming_code #Load Adult data base_path = "../../dataset/adult/" train_data, train_label, test_data, test_label, data_min, data_max = adult.load_data( base_path) bits_encoding = 128 nominal_length = {1: 64, 3: 64, 5: 64, 6: 64, 7: 64, 8: 64, 9: 64, 13: 64} nominal_length2 = {1: 30, 3: 30, 5: 30, 6: 30, 7: 30, 8: 30, 9: 30, 13: 30} ths = {} for index in data_max: ths[index] = thermometer.Thermometer(data_min[index], data_max[index], bits_encoding) train_bin = [] test_bin = [] i = 0 for data in train_data: train_bin.append(np.array([], dtype=bool)) for a in range(len(data)): if ths.has_key(a): binarr = ths[a].binarize(data[a]) #print "C ", binarr else: #binarr = hamming_code.get_code(data[a], nominal_length[a]) p = data[a] * nominal_length2[a]
#Load Australian data base_path = "../../dataset/australian/" #2/3 Test bits_encoding = 20 train_data, train_label, test_data, test_label, data_min, data_max = australian.load_3data(base_path) nominal_size = {0: 2, 3: 3, 4: 14, 5: 9, 7:2, 8:2, 10: 2, 11: 3} nominal_length = {0: 8, 3: 8, 4: 16, 5: 16, 7:8, 8:8, 10: 8, 11: 8} nominal_length2 = {0: 5, 3 : 5, 4: 5, 5: 5, 7: 5, 8:5, 10: 5, 11: 5} ths = {} for index in data_max: ths[index] = thermometer.Thermometer(data_min[index], data_max[index], bits_encoding) train_bin = [] test_bin = [] i = 0 for data in train_data: train_bin.append(np.array([], dtype=bool)) for a in range(len(data)): if ths.has_key(a): binarr = ths[a].binarize(data[a]) #print "C ", binarr else: #binarr = hamming_code.get_code(data[a], nominal_length[a]) p = data[a] * nominal_length2[a]