We develop a supervised dimensionality reduction method, called Lorentzian Discriminant Projection (LDP), for feature extraction and classification. Our method represents the str...
Because of the large variation across different environments, a generic classifier trained on extensive data-sets may perform sub-optimally in a particular test environment. In th...
Many semi-supervised learning algorithms only
deal with binary classification. Their extension to the
multi-class problem is usually obtained by repeatedly
solving a set of bina...
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
We introduce a simple order-based greedy heuristic for learning discriminative structure within generative Bayesian network classifiers. We propose two methods for establishing an...