Wang H.,Hefei University of Technology |
Wang H.,Kcji Laboratory of Process Optimization and Intelligent Decision making |
Luo H.,Hefei University of Technology |
Luo H.,Kcji Laboratory of Process Optimization and Intelligent Decision making
Journal of University of Science and Technology of China | Year: 2013
Although traditional manifold learning algorithms are common and effective dimension reduction methods, they still have calculating structure limits of their own, which lead to some problems such as inadequate data analyses and long calculation time. Therefore, on the basis of spectral clustering, a manifold learning algorithm named SCLLE (spectral clustering locally linear embedding) was proposed and its mechanisms as well as its advantages were demonstrated. Experiments with UCI and NCBI data sets show that the proposed algorithm has better recognition effect and computational performance.