Estimating the error rates of classifiers or regression models is a fundamental task in machine learning which has thus far been studied exclusively using supervised learning tech...
Pinar Donmez, Guy Lebanon, Krishnakumar Balasubram...
This book covers several topics such as Classification, Classical Statistical Methods, Modern Statistical Techniques, Machine Learning of Rules and Trees, Neural Networks
Methods ...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
The problem of learning is arguably at the very core of the problem of intelligence, both biological and artificial. In this paper we review our work over the last ten years in th...
This paper addresses feature selection techniques for classification of high dimensional data, such as those produced by microarray experiments. Some prior knowledge may be availa...