An ITERATIVE APPROACH To SUPPORT VECTOR MACHINES

摘要

The goal of this article is to investigate and suggest techniques for health condition monitoring and diagnosis using machine learning from sensor data. In particular, this article overviews and discusses support vector machine methods such as hard margin and soft margin problems. In order to investigate abnormalities and classify a large set of data an iterative Support Vector Machine algorithm was constructed. However, similar techniques can be applied to analyze and monitor for abnormality various other complex devices or even computer science theoretic methods.