How to optimize the parameters of trapezoidal membership function for an input data set using genetic programming ?

Hi,

I have a dataset of containing 4000 x 8 double values. I want to apply genetic programming to make it learn the optimal parameters (a,b,c,d) of the trapezoidal membership function (trapmf) of fuzzy logic toolbox, corresponding to each data point/row. What I am trying to do here is learn the fuzzy sets corresponding to each row (We assume the min and max of the column as the two boundary points for that input, i.e the constraint would be: min < a < b < c < d < max). Any suggestions on how to go about the problem ?

Thanks in advance,

Rajesh