SVM Decision Boundary Based Discriminative Subspace Induction
- Topics:
- Electrical and Electronic
- Source:
- Carnegie Mellon University
FREE Registration is required
Overview: This white paper deals with the formulating the problem of sufficient dimension reduction for classification in parallel terms as for regression. The report involves study of the problem of linear dimension reduction for classification, with a focus on sufficient dimension reduction, i.e., inducing subspaces without loss of discriminative information Disclosures of these connections lead to several meaningful observations. It also presents a novel space reduction algorithm that combines SVMand DBA, thus inheriting several appealing properties from kernel machines such as good generalization, weak assumption, and efficient computation.
(Is this item miscategorized? Does it need more tags? Let us know.)
Format: PDF | Size: 535KB | Date: Jun 2002 | Pages: 35



