Hinge Loss - A Steadfast Loss Evaluation Function for the SVM Classification Models in AI & MLby@sanjaykn170396
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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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@sanjaykn170396

Sanjay Kumar

Data scientist | ML Engineer | Statistician


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