Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...
The data sets for many of today's computer applications are too large to t within the computer's internal memory and must instead be stored on external storage devices su...
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
: For microarray based cancer classification, feature selection is a common method for improving classifier generalisation. Most wrapper methods use cross validation methods to eva...
This paper investigates methods to automatically infer structural information from large XML documents. Using XML as a reference format, we approach the schema generation problem ...