Now showing items 1-6 of 6
Incremental Support Vector Machine Classi cation
Using a recently introduced proximal support vector ma- chine classi er , a very fast and simple incremental support vector machine (SVM) classi er is proposed which is capable of modifying an existing linear classi ...
Privacy-Preserving Classification of Vertically Partitioned Data via Random Kernels
We propose a novel privacy-preserving support vector machine (SVM) classifier for a data matrix A whose input feature columns are divided into groups belonging to different entities. Each entity is unwilling to share its ...
Knowledge-Based Support Vector Machine Classi ers
Prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is introduced into a reformulation of a linear support vector machine classi er. The resulting formulation leads to a ...
Data Selection for Support Vector Machine Classifiers
The problem of extracting a minimal number of data points from a large dataset, in order to generate a support vector machine (SVM) classi er, is formulated as a concave minimization problem and solved by a nite number ...
Breast Tumor Susceptibility to Chemotherapy via Support Vector Machines
Support vector machines (SVMs), utilizing RNA signature measurements, were used to generate a classi er to distinguish breast cancer patients that are partial-responders to chemotherapy treatment, from patients that are ...
Knowledge-Based Nonlinear Kernel Classi ers
Prior knowledge in the form of multiple polyhedral sets, each belonging to one of two categories, is introduced into a reformulation of a nonlinear kernel support vector machine (SVM) classi er. The resulting formulation ...