Statistical learning theory has been regarded as one of the best theories for solving the small-sample learning problem on probability space. But it was difficult to deal with the problems on non-probability spaces and it mainly dealt with the noise-free case. In this paper, the key theorem with samples corrupted by zero-expect noise on chance space will be given and proven.
['Jun-Hua Li', 'Hai-Jun Li', 'Qiang He']
The key theorem of learning theory with samples corrupted by zero-expect noise on chance space