Investigating machine learning methods based on concepts of computational geometry

• Grant number: 07/03828-9
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2007
• End date: January 31, 2009
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Maria Do Carmo Nicoletti
• Grantee: Maria Do Carmo Nicoletti
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• City of the host institution: São Carlos

Abstract

Inductive machine learning is a very successful automatic learning model that has been largely implemented using many different formalisms and techniques. This project aims at the investigation of algorithms that belong to a specific class of machine learning techniques, the algorithms based on concepts related to computational geometry, particularly those based on the linear separability, convex hull and spanning trees. (AU)