I'm new to Machine Learning, so kindly ask for more details if required or do point me towards the resources I should read to have a better understanding. Lets say I have a data set consisting of these columns
"A" "B" "C" "D" "Target"
"Target" column is a boolean which I need to predict.
My task is to use Particle Swarm Optimization.
I know the theory behind PSO, I know it finds the fittest solution out of candidate solutions by using velocity, position, personal best and global best.
In R we have a function pso(func, S = 350, lim_inf, lim_sup, e = 0.0001, data = NULL, N = 500, prop = 0.2). The func here is objective function or fitness function.
I want to know how do I write a fitness function for my dataset.
Or have I misunderstood PSO and it's implementation. Please point me towards any useful resources.
