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...
In this paper we propose and test the use of hierarchical clustering for feature selection. The clustering method is Ward's with a distance measure based on GoodmanKruskal ta...
- Ever-increasing demands of space missions for data returns from their limited processing and communications resources have made the traditional approach of data gathering, data c...
Rajagopal Subramaniyan, Vikas Aggarwal, Adam Jacob...
Quantitative PET studies usually require invasive blood sampling from a peripheral artery to obtain an input function for accurate modelling. However, blood sampling is impractica...
Koon-Pong Wong, David Dagan Feng, Steven R. Meikle...
Cluster label quality is crucial for browsing topic hierarchies obtained via document clustering. Intuitively, the hierarchical structure should influence the labeling accuracy. H...