I am trying to build a linear regression model and one of my features when plotted against the output looks like a bell curve. So intuitively I figured that if I use the raw data for that feature my model won't be able to capture the non-linearity in it. So, I decided to use a Gaussian basis function only on that feature.
to do that I did the following code in Matlab x(:,1)=exp(-((x(:,1)-u).^2)./(2.*s.^2)) where u and s are the mean and standard deviation for that feature.
But I did not get any improvement in my model. Is there something wrong I am doing, or maybe perhaps something fundamentally wrong( I am new to machine learning and Data analytics).