SVM Constraint Discovery using KNN applied to the Identification of Cyberbullying
نویسنده
چکیده
In the context of classifying cyberbullying comments, we introduce a k-nearest neighbor/support vector machine hybrid model. A crucial insight into the training of support vector machines is that the training and the resulting model only depend on a few select points of the training data the support vectors that represent constraints on the implicit decision surfaces of the models. As part of our hybrid model we propose to identify support vector candidates in the training data using a modified k-nearest neighbor algorithm. The reduced training data is then used to train the support vector machine.
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