Applications of SVM in Real World SVMs depends on supervised learning algorithms. The aim of using SVM is to correctly classify unseen data. SVMs have a number of applications in several fields. Some common applications of SVM are- Face detection – SVMc classify parts of the image as a face and non-face and create a square boundary around the face. Text and hypertext categorization – SVMs all…
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