AURA (Advanced Uncertain Reasoning Architecture) is a parallel pattern matching technology intended for high-speed approximate search and match operations on large unstructured dat...
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Feature subset selection presents a common challenge for the applications where data with tens or hundreds of features are available. Existing feature selection algorithms are mai...
Multilayer perceptrons are often trained using error backpropagation (BP). BP training can be done in either a batch or continuous manner. Claims have frequently been made that bat...
Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...