Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Traditional visualization techniques for multidimensional data sets, such as parallel coordinates, glyphs, and scatterplot matrices, do not scale well to high numbers of dimension...
Jing Yang, Matthew O. Ward, Elke A. Rundensteiner,...
Background: Gene Ontology (GO) is a standard vocabulary of functional terms and allows for coherent annotation of gene products. These annotations provide a basis for new methods ...
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
For a very long time, it has been considered that the only way of automatically extracting similar groups of words from a text collection for which no semantic information exists ...