Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Combined classifiers can show better performance than the best single classifier used in isolation, while involving little additional computational effort. This is because different classifier can potentially offer complementary information about the pattern and group decisions can take the advantage of the benefit of combining multiple classifiers in making final decision.   propose a new combining method, which harness the local confidence of each classifier in the combining process. This method learns the local confidence of each classifier using training data and if an unknown data is given, the learned knowledge is used to evaluate the outputs of individual classifiers. An empirical evaluation using five real data sets has shown that this method achieves a promising performance and outperforms the best single classifiers and other known combining methods  tried.
['Eunju Kim', 'Wooju Kim', 'Yillbyung Lee']
I am writing a research paper on a idea Classifier Fusion Using Local Confidence
[{"from": "human", "value": "I am writing a research paper on a idea Classifier Fusion Using Local Confidence"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Combined classifiers can show better performance than the best single classifier used in isolation, while involving little additional computational effort. This is because different classifier can potentially offer complementary information about the pattern and group decisions can take the advantage of the benefit of combining multiple classifiers in making final decision.   propose a new combining method, which harness the local confidence of each classifier in the combining process. This method learns the local confidence of each classifier using training data and if an unknown data is given, the learned knowledge is used to evaluate the outputs of individual classifiers. An empirical evaluation using five real data sets has shown that this method achieves a promising performance and outperforms the best single classifiers and other known combining methods  tried."}]