⚡ optim
Optimization Algorithms
23 functions
875 lines
Gradient-based
📖 Overview
Optimization algorithms: gradient descent, Newton, BFGS, simulated annealing, genetic algorithms.
🚀 Quick Start
import optim
function f(x: float) -> float do
return (x - 2.0) * (x - 2.0)
end
let result = optim.minimize(f, 0.0)?
println("Minimum at x = {}", result.x)