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]
