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I take that it's a 'kind' of decision tree or random forest with gradient boosting, so usually it 'can' run faster on a CPU if optimized than on a GPU (if I'm n
by FractalNerve 9y ago
I take that it's a 'kind' of decision tree or random forest with gradient boosting, so usually it 'can' run faster on a CPU if optimized than on a GPU (if I'm not mistaken). That's at least what I get from BigML's offering.
edit: Can you provide insight?
- loserboss 9y agoIt is not decision tree or any machine learning algorithm. It is a local search algorithm that probably has simulated annealing or tabu search as a metaheuristic. Although, they probably segment the deliveries to some common starting points and the problem size is reduced significantly - maybe to around thousand orders per starting point. Research can easily optimize thousands of deliveries very effectively.
- FractalNerve 9y agowow I'm intrigued and haven't even heard of tabu search before you mentioned it, thank you very much! You surely are my hero today loserboss =)