Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Multi-label classification is to assign an instance to multiple classes. Naive Bayes (NB) is one of the most popular algorithms for pattern recognition and classification. It has a high performance in single label classification. It is naturally extended for multi-label classification under the assumption of label independence. As  know, NB is based on a simple but unrealistic assumption that attributes are conditionally independent given the class. Therefore, a double ighted NB (DWNB) is proposed to demonstrate the influences of predicting different labels based on different attributes. Our DWNB utilizes the niching cultural algorithm (NLA) to determine the ight configuration automatically. Our experimental results show that our proposed DWNB outperforms NB and its extensions significantly in multi-label classification.
['Xuesong Yan', 'Qinghua Wu', 'Victor S. Sheng']
I am writing a research paper on a idea A Double Weighted Naive Bayes with Niching Cultural Algorithm for Multi-Label Classification
[{"from": "human", "value": "I am writing a research paper on a idea A Double Weighted Naive Bayes with Niching Cultural Algorithm for Multi-Label Classification"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Multi-label classification is to assign an instance to multiple classes. Naive Bayes (NB) is one of the most popular algorithms for pattern recognition and classification. It has a high performance in single label classification. It is naturally extended for multi-label classification under the assumption of label independence. As  know, NB is based on a simple but unrealistic assumption that attributes are conditionally independent given the class. Therefore, a double ighted NB (DWNB) is proposed to demonstrate the influences of predicting different labels based on different attributes. Our DWNB utilizes the niching cultural algorithm (NLA) to determine the ight configuration automatically. Our experimental results show that our proposed DWNB outperforms NB and its extensions significantly in multi-label classification."}]