Now showing items 1-6 of 6
RSVM: Reduced Support Vector Machines
An algorithm is proposed which generates a nonlinear kernel-based separating surface that requires as little as 1% of a large dataset for its explicit evaluation. To generate this nonlinear surface, the entire dataset ...
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 ...
Survival-Time Classi cation of Breast Cancer Patients
The identi cation of breast cancer patients for whom chemother- apy could prolong survival time is treated here as a data mining prob- lem. This identi cation is achieved by clustering 253 breast cancer patients into ...
Cross-Validation, Support Vector Machines and Slice Models
We show how to implement the cross-validation technique used in ma- chine learning as a slice model. We describe the formulation in terms of support vector machines and extend the GAMS/DEA interface to allow for e cient ...
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 Mining via Support Vector Machines
Support vector machines (SVMs) have played a key role in broad classes of problems arising in various elds. Much more recently, SVMs have become the tool of choice for problems arising in data classi - cation and mining. ...