Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
—Identification of nodes relevant to a given node in a relational network is a basic problem in network analysis with great practical importance. Most existing network analysis ...
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...
Despite recent progress in high-throughput experimental studies, systems level visualization and analysis of large protein interaction networks (ppi) remains a challenging task, g...
Boon-Siew Seah, Sourav S. Bhowmick, Charles Forbes...