-
Optimization (4/n): Genetic Algorithm(s) (2/3)
Intro This week, I’ll make it short, and instead of boring with code and explanations, I thought I’d just show an example output… Results This is a genetic algorithm in action: A population “evolves” (reproduces, “selection of the fittest”, iterate) towards an objective. Complexity of many local minima don’t seem to be an issue for…
-
Optimization (3/n): Simulated Annealing
Intro Continuing with this simple “series” (see here and here), I implement the next algorithm proposed by the reference book, but in R. This time around, it’s the turn of “Simulated Annealing”. Nice parallel I like how the concept of molecules excitement and temperatures is used for this algorithm. All in all, it’s a bit…
-
Optimization (2/n): Gradient Descent
Intro So I keep going with the reference book for a while. BTW, the book can be found here (NOT a referral or anything, I don’t make money out of this, it’s just a pointer to one place you can find it). And yes, the book is in Spanish… So one of the first algorithms…