Analyzing the quality of data prior to constructing data mining models is emerging as an important issue. Algorithms for identifying noise in a given data set can provide a good me...
Jason Van Hulse, Taghi M. Khoshgoftaar, Haiying Hu...
Composition of temporal and spatial properties of real world objects in a unified data framework results into Moving Object Databases (MOD). MODs are able to process, manage and a...
Several advanced applications, such as those dealing with the Web, need to handle data whose structure is not known a-priori. Such requirement severely limits the applicability of ...
The most basic assumption used in statistical learning theory is that training data and test data are drawn from the same underlying distribution. Unfortunately, in many applicati...
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...