Not quite unreasonable effectiveness of machine learning algorithms

04/07/2018
by   Egor Illarionov, et al.
0

State-of-the-art machine learning algorithms demonstrate close to absolute performance in selected challenges. We provide arguments that the reason can be in low variability of the samples and high effectiveness in learning typical patterns. Due to this fact, standard performance metrics do not reveal model capacity and new metrics are required for the better understanding of state-of-the-art.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset