a support vector machine-based fuzzy classification technique
Abstract
A unique form of learning machine based on statistical learning theory is the support vector machine (SVM). SVMs have been widely employed in classification, regression, and pattern recognition because of their strong generalisation capabilities. This research proposes a novel fuzzy classification method (FCM) based on SVM for data containing numerical condition attributes and decision attributes. This process initially confuses some classes (linguistic words)' choice characteristics before training the decision function (classifier). The decision function provides the matching class and its membership degree as a fuzzy decision for a fresh sample rather than predicting the value of its decision characteristic.
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