Dimensional reduction may be effective in order to compress data without loss of essential information. Also, it may be useful in order to smooth data and reduce random noise. The...
We propose a unified manifold learning framework for semi-supervised and unsupervised dimension reduction by employing a simple but effective linear regression function to map the ...
Feiping Nie, Dong Xu, Ivor Wai-Hung Tsang, Changsh...
Abstract. The upper-level ontologies are theories that capture the most common concepts, which are relevant for many of the tasks involving knowledge extraction, representation, an...
Background: Phylogenetic relationships between genes are not only of theoretical interest: they enable us to learn about human genes through the experimental work on their relativ...
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...