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The concepts of centrality and diversity are highly important in search algorithms, and play central roles in applications of artificial intelligence (AI), machine learning (ML), social networks, and pattern recognition.
This work reviews the state of the art in SVM and perceptron classifiers. The weight vector associated with SVM is obtained by a linear combination of some of the boundary and noisy vectors. Even though SVMs have popularized the kernel trick, in most of the practical applications that are high-dimensional, linear SVMs are popularly used.
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