The use of compression algorithms in machine learning tasks such as clustering and classification has appeared in a variety of fields, sometimes with the promise of reducing probl...
In this work we consider the problem of binary classification where the classifier may abstain instead of classifying each observation, leaving the critical items for human evaluat...
Abstract—Frameworks are a key technology to reduce software development costs and shorten the time-to-market. However, framework complexity presents reuse problems that limit its...
Emergency department free-text chief complaints (CCs) are a major data source for syndromic surveillance. CCs need to be classified into syndromic categories for subsequent automa...
Hsin-Min Lu, Daniel Zeng, Lea Trujillo, Ken Komats...
Text classification in the medical domain is a real world problem with wide applicability. This paper investigates extensively the effect of text representation approaches on the p...
Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Be...