A locality correlation preserving support vector machine
We propose a novel support vector machine like classification algorithm LCPSVM. LCPSVM combines the idea of margin maximization between classes and local correlation preservation of class data. It is shown that SVM and other related algorithms can be obtained as special cases of LCPSVM. Experiments under different conditions are performed, and the results are discussed.
locality correlation preservation support vector machine kernel methods fuzzy membership