Though many tools are available to help programmers working on change tasks, and several studies have been conducted to understand how programmers comprehend systems, little is kn...
Detecting outliers in data is an important problem with interesting applications in a myriad of domains ranging from data cleaning to financial fraud detection and from network i...
Gustavo Henrique Orair, Carlos Teixeira, Ye Wang, ...
In this paper we demonstrate how a qualitative framework for decision making can be used to model scenarios from experimental economic studies and we show how our approach explains...
Trevor J. M. Bench-Capon, Katie Atkinson, Peter Mc...
It is well-known that naive Bayes performs surprisingly well in classification, but its probability estimation is poor. In many applications, however, a ranking based on class prob...
Fault prediction models still seem to be more popular in academia than in industry. In industry expert estimations of fault proneness are the most popular methods of deciding wher...