Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Feature selection is a ll-researched problem, which can improve the network performance and speed up the training of the network. ,  proposed an effective feature selection scheme for SVM using the hybrid of enhanced genetic algorithm and mutual information, in which mutual information beten each input and each output of the data set is employed in mutation in evolutionary process to purposefully guide search direction based on some criterions. In order to avoid the noise fitness evaluation, in evaluating the fitness of an input subset, a SVM should adaptively adjust its parameters to obtain the best performance of network, so an enhanced GA is used to simultaneously evolve the input features and the parameters of SVM. By examining two real financial time series, the simulation of three different methods of feature selection shows that the feature selection using the hybrid of GA and MI can reduce the dimensionality of inputs, speed up the training of the network and get better performance.
['Chunkai Zhang', 'Hong Hu']
I am writing a research paper on a idea Feature Selection in SVM Based on the Hybrid of Enhanced Genetic Algorithm and Mutual Information
[{"from": "human", "value": "I am writing a research paper on a idea Feature Selection in SVM Based on the Hybrid of Enhanced Genetic Algorithm and Mutual Information"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Feature selection is a ll-researched problem, which can improve the network performance and speed up the training of the network. ,  proposed an effective feature selection scheme for SVM using the hybrid of enhanced genetic algorithm and mutual information, in which mutual information beten each input and each output of the data set is employed in mutation in evolutionary process to purposefully guide search direction based on some criterions. In order to avoid the noise fitness evaluation, in evaluating the fitness of an input subset, a SVM should adaptively adjust its parameters to obtain the best performance of network, so an enhanced GA is used to simultaneously evolve the input features and the parameters of SVM. By examining two real financial time series, the simulation of three different methods of feature selection shows that the feature selection using the hybrid of GA and MI can reduce the dimensionality of inputs, speed up the training of the network and get better performance."}]