import numpy as np
import sys
sys.path.insert(0, '../')
import Regressor
data = open('yacht_hydrodynamics.data', 'r')
row_list = []
for line in data:
line = line.strip()
line_list = line.split(' ')
index = -1
for l in line_list:
index += 1
if l == ' ':
del line_list[index]
if l == '':
del line_list[index]
line_list[index] = line_list[index].rstrip()
if len(line_list) != 7:
print line_list
row_list.append(line_list)
output_list = list(row[6] for row in row_list)
Regressor.callAllRegressor(np.array(row_list).astype(float), np.array(output_list).astype(float), len(row_list))
import numpy as np
import sys
sys.path.insert(0, '../')
import Regressor
park_file = open('parkinsons_updrs.data', 'r');
b = []
x = list((line.split(',') for line in park_file))
motor_UPDRS_list = []
total_UPDRS_list = []
for attribute in x:
total_UPDRS_list.append(attribute[5])
motor_UPDRS_list.append(attribute[4])
for val in x:
del val[4]
del val[5]
# Train the model using the training sets
print 'MOTOR'
Regressor.callAllRegressor(np.array(x).astype(float), np.array(motor_UPDRS_list).astype(float), len(x))
print 'TOTAL'
Regressor.callAllRegressor(np.array(x).astype(float), np.array(total_UPDRS_list).astype(float), len(x))
