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.
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