Review: Support Vector Machines in Pattern Recognition
Parashjyoti Borah, Deepak Gupta · International Journal of Engineering and Technology · 2017
SVM is extensively used in pattern recognition because of its capability to classify future unseen data and its' good generalization performance.Several algorithms and models have been proposed for pattern recognition that uses SVM for classification.These models proved the efficiency of SVM in pattern recognition.Researchers have compared their results for SVM with other traditional empirical risk minimization techniques, such as Artificial Neural Network, Decision tree, etc.Comparison results show that SVM is superior to these techniques.Also, different variants of SVM are developed for enhancing the performance.In this paper, SVM is briefed and some of the pattern recognition applications of SVM are surveyed and briefly summarized.