Using Genetic Programming with Prior Formula Knowledge to Solve Symbolic Regression Problem

Algorithm 2

.

Input: , PFKB, ( is the dataset; is the number of formula models whose features can show the dataset)

Output: (formula model vector which are used in generating the initial population of )

() temp = predictModel(PFKB, ) // as the intermediate data, it is the original result that exploit the PFKB

  to predict without sorting by the fitness

() temp = sortModelByFit(temp) // sort the models in order of decreasing fitness

() for = 1 : 

()  () = temp( )

() end

() return