svalordev

# Coefficients
print('Coefficients: \n', regressor.coef_)
# The mean squared error
print("Mean squared error: %.2f" % np.mean((regressor.predict(X_test) - y_test) ** 2))
# Explained variance score: 1 is perfect prediction
print('Variance score: %.2f' % regressor.score(X_test, y_test))

svalordev

Keybase proof

I hereby claim:

• I am shaurya-blip on github.
• I am sblipdev (https://keybase.io/sblipdev) on keybase.
• I have a public key ASChL-n6owvUHN6DHVTnBiyfkQDOkUStcFKnNUZ51tWm2Ao

To claim this, I am signing this object:

svalordev

def load_dotdoe(doe_path=None):
    if doe_path is None:
        f = open('.doe', 'r')
    else:
        f = open(doe_path, 'r')

    text = f.read()
    lines = text.split('\n')

    dictionary = {}