In recent years, the technological advances in mapping genes have made it increasingly easy to store and use a wide variety of biological data. Such data are usually in the form o...
Symbolic data analysis aims at generalizing some standard statistical data mining methods, such as those developed for classification tasks, to the case of symbolic objects (SOs). ...
This paper develops the concept of usefulness in the context of supervised learning. We argue that usefulness can be used to improve the performance of classification rules (as me...
Gholamreza Nakhaeizadeh, Charles Taylor, Carsten L...
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
Weblogs and message boards provide online forums for discussion that record the voice of the public. Woven into this mass of discussion is a wide range of opinion and commentary a...
Natalie S. Glance, Matthew Hurst, Kamal Nigam, Mat...