Successive Least Squares Support Vector Machine for Multiple Instance Classification

摘要

Multiple instance learning is an important and on-going research subject in machine learning. In this paper, we propose a new successive least squares support vector algorithm for multiple instance classification. The proposed algorithm uses an iterative strategy by solving a linear system of equations and a quadratic programming problem alternatively. Numerical experiments on the benchmark data sets show that the proposed algorithm has promising performance.