This paper presents an autonomous algorithm for discovering exception rules from data sets. An exception rule, which is defined as a deviational pattern to a well-known fact, exhi...
In the area of data mining, the discovery of valuable changes and connections (e.g., causality) from multiple data sets has been recognized as an important issue. This issue essen...
Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions c...
Classification methods from statistical pattern recognition, neural nets, and machine learning were applied to four real-world data sets. Each of these data sets has been previous...
With a few exceptions, discriminative training in statistical machine translation (SMT) has been content with tuning weights for large feature sets on small development data. Evid...