Information discriminative extreme learning machine

Extreme learning machine (ELM) has become one of the new research hotspots in the field of pattern recognition and machine learning. However, the existing extreme learning machine algorithms cannot better use identification information of data. Aiming at solving this problem, we propose a regularized extreme learning machine (algorithm) based on discriminative information (called IELM). In order to evaluate and verify the effectiveness of the proposed method, experiments use widely used image data sets. The comparative experimental results show that the proposed algorithm in the paper can significantly improve the classification performance and generalization ability of ELM.