Stochastic inference is defined as an accuracy measure over the decision of a learning algorithm. The typical accuracy measures used for pattern recognition are confidence and credibility. These measures are challenging to define, compute and exploit to improve pattern recognition. In this research we define a confidence and a credibility measure based on the VC dimension of a learning algorithm defined by Vapnik and Chervonenkis and the notion of algorithmic randomness as defined by Kolmogorov. The resulting confidence and credibility measures are applied to pattern recognition methods to...
Stochastic inference is defined as an accuracy measure over the decision of a learning algorithm. The typical accuracy measures used for pattern recog...
