Improved Isomap Algorithm Based on Supervision

Abstract

It focuses Isomap isometric embedding algorithm is proposed to improve supervised isometric embedding algorithm (SIsomap). Both supervised manifold learning algorithm, using the introduction of adjustable parameters in the form of classes in the classification problem for the effective use of information, making the manifold learning algorithms for classification classification problems have a stronger effect. Finally, through a series of experiments to fully illustrate the proposed improvement of the effectiveness of the algorithm, the proposed oversight of the manifold learning algorithm can more effectively enhance manifold learning algorithms for classification problems