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[NEW ALGORITHM] Implementing Support Vector Machines (SVM) Algorithm #954
Support Vector Machines (SVM) is a supervised machine learning algorithm primarily used for classification tasks, although they can also be applied to regression. The core idea behind SVM is to find a hyperplane that best separates different classes in the feature space, maximizing the margin between the closest data points (support vectors) of the classes. This characteristic allows SVMs to generalize well to unseen data.
@pankaj-bind sir, I raised the issue and someone else submitted the PR without even getting assigned. But sir please assign me this issue instead of closing it since I was waiting for the assigning of issue
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Support Vector Machines (SVM) is a supervised machine learning algorithm primarily used for classification tasks, although they can also be applied to regression. The core idea behind SVM is to find a hyperplane that best separates different classes in the feature space, maximizing the margin between the closest data points (support vectors) of the classes. This characteristic allows SVMs to generalize well to unseen data.
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new algorithm, gssoc-ext, hacktoberfest, level1
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