We automatically classify verbs into lexical semantic classes, based on distributions of indicators of verb alternations, extracted from a very large annotated corpus. We address ...
In some classification problems, like the detection of illnesses in patients, classes are very unbalanced and the misclassification costs for different classes vary significantly....
Abstract. We propose an algorithm for Sparse Bayesian Classification for multi-class problems using Automatic Relevance Determination(ARD). Unlike other approaches which treat mult...
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
In this paper, we present a new rule induction algorithm for machine learning in medical diagnosis. Medical datasets, as many other real-world datasets, exhibit an imbalanced clas...