Hinge Loss - A Steadfast Loss Evaluation Function for the SVM Classification Models in AI & ML
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Machine learning is nothing but an optimisation problem. Researchers use an algebraic acme called “Losses” in order to optimise the machine learning space defined by a specific use case. Hinge loss is a function popularly used in support vector machine algorithms to measure the distance of data points from the decision boundary.
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