Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a semi-supervised sub-manifold discriminant analysis algorithm. To separate each sub-manifold constructed by each class,  define the within-manifold scatter, beten-manifold scatter and total-manifold scatter matrices. The scatter matrices are robust to outlier and diverse-density clusters. Kernelization and direct non-linear embedding are also developed. Experimental results show that our approach can give competitive results in comparison to the state-of-the-art algorithms.
['Yangqiu Song', 'Feiping Nie', 'Changshui Zhang']
I am writing a research paper on a idea Semi-supervised sub-manifold discriminant analysis
[{"from": "human", "value": "I am writing a research paper on a idea Semi-supervised sub-manifold discriminant analysis"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  present a semi-supervised sub-manifold discriminant analysis algorithm. To separate each sub-manifold constructed by each class,  define the within-manifold scatter, beten-manifold scatter and total-manifold scatter matrices. The scatter matrices are robust to outlier and diverse-density clusters. Kernelization and direct non-linear embedding are also developed. Experimental results show that our approach can give competitive results in comparison to the state-of-the-art algorithms."}]