Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Support Vector Machine (SVM) is a porful tool for binary classification. Numerous methods are known to fuse several binary SVMs into multi-class (MC) classifiers. These methods are efficient, but an accurate study of the misclassified items leads to notice two sources of mistakes: (1) the response of each classifier does not use the entire information from the SVM, and (2) the decision method does not use the entire information from the classifier responses. ,  present a method which partially prevents these two losses of information by applying Belief Theories (BTs) to SVM fusion, while keeping the efficient aspect of the classical methods.
['Thomas Burger', 'Oya Aran', 'Alice Caplier']
I am writing a research paper on a idea Modeling Hesitation and Conflict: A Belief-Based Approach for Multi-class Problems
[{"from": "human", "value": "I am writing a research paper on a idea Modeling Hesitation and Conflict: A Belief-Based Approach for Multi-class Problems"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Support Vector Machine (SVM) is a porful tool for binary classification. Numerous methods are known to fuse several binary SVMs into multi-class (MC) classifiers. These methods are efficient, but an accurate study of the misclassified items leads to notice two sources of mistakes: (1) the response of each classifier does not use the entire information from the SVM, and (2) the decision method does not use the entire information from the classifier responses. ,  present a method which partially prevents these two losses of information by applying Belief Theories (BTs) to SVM fusion, while keeping the efficient aspect of the classical methods."}]