Semi-Supervised Extreme Learning Machine using L1-Graph

Hongwei Zhao
2018 International Journal of Performability Engineering  
The semi-supervised learning method has been widely used in the field of pattern recognition. Semi-supervised Extreme Learning Machine (SELM) is a typical semi-supervised learning algorithm. The graph construction result of the sample data has a tremendous impact on the SELM algorithm. In traditional graph composition methods such as Laplace graph, LLE graph and K neighboring graph, neighborhood parameters are specified by humans. If there are noises or uneven distribution in the data, the
more » ... the data, the results are not very good. This paper proposes a SELM algorithm based on L1-Graph, which features no specifying parameters, is robust against noise, has a sparse solution and so on. The experiment confirms the effectiveness of the method.
doi:10.23940/ijpe.18.04.p2.603610 fatcat:jxrzzhx6jbdulihsv6qozyodra