def linear_reg(df, Y, binary=False, ridge=False, sigmoid=False):
means = []
columns = [col for col in df.columns if (col != "is_spam" and col != "MEDV" and col != "y")]
if ridge:
w = mystats.get_linridge_w(df[columns], df[Y], binary)
else:
for col in df.columns:
mean = df[col].mean()
means.append(mean)
df[col] -= mean
w = mystats.get_linreg_w(df[columns], df[Y])
print ("w:")
print (w)
predict = mystats.predict(df[columns], w, binary, means=means)
error = mystats.get_error(predict, df[Y], binary)
return error
