Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  consider music classification problems. A typical machine learning approach is to use support vector machines with some kernels. This approach, hover, does not seem to be successful enough for classifying music data in our experiments. ,  follow an alternative approach.  employ a (dis)similarity-based learning framework proposed by Wang et al. This (dis)similarity-based approach has a theoretical guarantee that one can obtain accurate classifiers using (dis)similarity measures under a natural assumption.  demonstrate the effectiveness of our approach in computational experiments using Japanese MIDI data.
['Yoko Anan', 'Kohei Hatano', 'Hideo Bannai', 'Masayuki Takeda']
I am writing a research paper on a idea Music Genre Classification using Similarity Functions
[{"from": "human", "value": "I am writing a research paper on a idea Music Genre Classification using Similarity Functions"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  consider music classification problems. A typical machine learning approach is to use support vector machines with some kernels. This approach, hover, does not seem to be successful enough for classifying music data in our experiments. ,  follow an alternative approach.  employ a (dis)similarity-based learning framework proposed by Wang et al. This (dis)similarity-based approach has a theoretical guarantee that one can obtain accurate classifiers using (dis)similarity measures under a natural assumption.  demonstrate the effectiveness of our approach in computational experiments using Japanese MIDI data."}]