A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine.

ABSTRACT: For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic data selection mechanism. In this paper, inspired by human learning process, a novel classification algorithm based on incremental semi-supervised support vector machine (SVM) is proposed. Through the analysis of prediction confidence of samples and data distribution in a changing environment, a "soft-start" approach, a data selection mechanism and a data cleaning mechanism are designed, which complete the construction of our incremental semi-supervised learning system. Noticeably, with the ingenious design procedure of our proposed algorithm, the computation complexity is r

SUBMITTER: Gao F 

PROVIDER: S-EPMC4537225 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature