Given a decision problem P and a probability distribution over binary strings, for each n, draw independently an instance xn of P of length n. What is the probability that there i...
Andreas Blass, Yuri Gurevich, Vladik Kreinovich, L...
Combinations of multiple classifiers have been found to be consistently more accurate than a single classifier. The construction of multiple independent classifiers, however, is t...
Torsten Rohlfing, Daniel B. Russakoff, Calvin R. M...
Binary decision trees based on univariate splits have traditionally employed so-called impurity functions as a means of searching for the best node splits. Such functions use estim...
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
We consider the problem of binary hypothesis testing using binary decisions from independent and identically distributed (i.i.d). sensors. Identical likelihood-ratio quantizers wit...