An ensemble of classifiers is a set of classifiers whose predictions are combined in some way to classify new instances. Early research has shown that, in general, an ensemble of ...
The standard kNN algorithm suffers from two major drawbacks: sensitivity to the parameter value k, i.e., the number of neighbors, and the use of k as a global constant that is ind...
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
This paper describes the efforts undertaken in an international research project LT4eL from the perspective of one of the participating languages, Czech. The project aims at explo...
Preferences in constraint problems are common but significant in many real world applications. In this paper, we extend our conditional and composite CSP (CCCSP) framework, managi...
The paper presents a new approach to the problem of paraphrase identification. The new approach extends a previously proposed method for the task of textual entailment. The relati...
Vasile Rus, Philip M. McCarthy, Mihai C. Lintean, ...
Spatial or temporal reasoning is an important task for many applications in Artificial Intelligence, such as space scheduling, navigation of robots, etc. Several qualitative appro...