New Fuzzy Multi-Class Method to Train SVM Classifier

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Provided by: IARIA
Topic: Data Management
Format: PDF
In this paper, the authors present a new classification method based on Support Vector Machine (SVM) to treat multi-class problems. In the context of multi-class problems, they have to separate large number of classes. SVM becomes an important machine learning tool to handle multi-class problems. Usually, SVM classifiers are implemented to deal with binary classification problems. In order to handle multiclass problems, they present a new method that builds dynamically a hierarchical structure from training data. Their multiclass method is based on three main concepts : hierarchical classification, fuzzy logic and SVM. They combine multiple binary SVMs to solve multi-class problems.
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