Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Optimizing the parameters of kernel methods is an unsolved problem.  report an experimental evaluation and a consideration of the parameter dependences of kernel mutual subspace method (KMS). The following KMS parameters are considered: Gaussian kernel parameters, the dimensionalities of dictionary and input subspaces, and the number of canonical angles.  evaluate the recognition accuracies of KMS through experiments performed using the ETH- 80 animal database. By searching exhaustively for optimal parameters,  obtain 100% recognition accuracy, and some experimental results suggest relationships beten the dimensionality of subspaces and the degrees of freedom for the motion of objects. Such results imply that KMS achieves a high recognition rate for object recognition with optimized parameters.
['Hitoshi Sakano', 'Osamu Yamaguchi', 'Tomokazu Kawahara', 'Seiji Hotta']
I am writing a research paper on a idea On the behavior of kernel mutual subspace method
[{"from": "human", "value": "I am writing a research paper on a idea On the behavior of kernel mutual subspace method"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Optimizing the parameters of kernel methods is an unsolved problem.  report an experimental evaluation and a consideration of the parameter dependences of kernel mutual subspace method (KMS). The following KMS parameters are considered: Gaussian kernel parameters, the dimensionalities of dictionary and input subspaces, and the number of canonical angles.  evaluate the recognition accuracies of KMS through experiments performed using the ETH- 80 animal database. By searching exhaustively for optimal parameters,  obtain 100% recognition accuracy, and some experimental results suggest relationships beten the dimensionality of subspaces and the degrees of freedom for the motion of objects. Such results imply that KMS achieves a high recognition rate for object recognition with optimized parameters."}]