Abstract—We experimentally evaluate bagging and seven other randomizationbased approaches to creating an ensemble of decision tree classifiers. Statistical tests were performed o...
Robert E. Banfield, Lawrence O. Hall, Kevin W. Bow...
We consider the problem of constructing decision trees for entity identification from a given relational table. The input is a table containing information about a set of entities...
Venkatesan T. Chakaravarthy, Vinayaka Pandit, Samb...
Abstract. Most of the work in Machine Learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
We describe a quantum black-box network computing the majority of N bits with zerosided error using only 2 3 N + O( N log( -1 log N)) queries: the algorithm returns the correct an...
Thomas P. Hayes, Samuel Kutin, Dieter van Melkebee...
We consider how an agent should update her uncertainty when it is represented by a set P of probability distributions and the agent observes that a random variable X takes on valu...