Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass case has been shown to be equivalent to linear re...
Regularized kernel discriminant analysis (RKDA) performs linear discriminant analysis in the feature space via the kernel trick. Its performance depends on the selection of kernel...
We develop a novel multi-class classification method based on output codes for the problem of classifying a sequence of amino acids into one of many known protein structural class...
Eugene Ie, Jason Weston, William Stafford Noble, C...
Abstract—We present the query-by-description (QBD) component of “Kandem,” a time-aware music retrieval system. The QBD system we describe learns a relation between descriptiv...
Kernels are two-placed functions that can be interpreted as inner products in some Hilbert space. It is this property which makes kernels predestinated to carry linear models of l...