def main():
#create the training & test sets, skipping the header row with [1:]
dataset = genfromtxt(open('train.csv','r'), delimiter=',', dtype='int')[1:]
target = [x[0] for x in dataset]
train = [x[1:] for x in dataset]
test = genfromtxt(open('test.csv','r'), delimiter=',', dtype='int')[1:]
#create and train the random forest
#multi-core CPUs can use: rf = RandomForestClassifier(n_estimators=100, n_jobs=2)
rf = RandomForestClassifier(n_estimators=100)
rf.fit(train, target)
predicted_value = [x for x in rf.values(test)]
savetxt('submission.csv', predicted_value, delimiter=',', fmt='%f')
