Core Set Extreme Learning Machine

Shuxia Lu1, Bin Liu2, Caihong Jiao1

1Key Lab. In Machine Learning and Computational Intelligence College of Mathematics and Computer Science, Hebei University Baoding 071002, China

2 School of Mechanical and Vehicular Engineering, Beijing Institute of Technology Beijing 100081, China

Abstract: A core set extreme learning machine (CSELM) approach is proposed in order to deal with large datasets classification problem. In the first stage, the core set can be obtained efficiently by using the generalized core vector machine (GCVM) algorithm. For the second stage, the extreme learning machine (ELM) can be used to implement classification for much larger datasets. Experiments show that the CSELM has comparable performance with SVM and ELM implementations, but is faster on large datasets.

Keywords: Core vector machine; Extreme learning machine; Support vector machine; Core set