from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_absolute_error

testTarget = np.loadtxt('testTarget.csv')
testInput  = np.loadtxt('testInput.csv')

def sci_RF(samplesX, samplesY, n_estimators):
	train_x, test_x, train_y, test_y = train_test_split(samplesX, samplesY, test_size=0.2)
	model = RandomForestRegressor(n_estimators, n_jobs=-1)
	model.fit(train_x, train_y)
	imp = model.feature_importances_
	print 'Train MAE: {}'.format(mean_absolute_error(train_y, model.predict(train_x)))
	print 'Test MAE: {}'.format(mean_absolute_error(test_y, model.predict(test_x)))
	return imp


imp = sci_RF(trainInput, trainTarget, 2500)
print(imp)