Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
In this paper, we present a new interpretation of AdaBoost.ECC and AdaBoost.OC. We show that AdaBoost.ECC performs stage-wise functional gradient descent on a cost function, defin...
Despite of the large number of algorithms developed for clustering, the study on comparing clustering results is limited. In this paper, we propose a measure for comparing cluster...
This paper addresses the problem of finding a small and coherent subset of points in a given data. This problem, sometimes referred to as one-class or set covering, requires to fi...
In this work, we present a new bottom-up algorithmfor decision tree pruning that is very e cient requiring only a single pass through the given tree, and prove a strong performanc...