Over the last few years, two of the main research directions in machine learning of natural language processing have been the study of semi-supervised learning algorithms as a way...
In this paper we perform an empirical evaluation of supervised learning on highdimensional data. We evaluate performance on three metrics: accuracy, AUC, and squared loss and stud...
This paper introduces a new method for supervised discretization based on interval distances by using a novel concept of neighborhood in the target's space. The proposed metho...
In this article, we describe a feature selection algorithm which can automatically find relevant features for multiple instance learning. Multiple instance learning is considered a...
Kernel-based systems are currently very popular approaches to supervised learning. Unfortunately, the computational load for training kernel-based systems increases drastically wit...