SUPPORT VECTOR MACHINE ALGORITHM

The Support Vector Machine algorithm was analyzed in this study. The Support Vector Machine (SVM) algorithm is a powerful and widely used machine learning algorithm for classification and regression tasks. It belongs to the family of supervised learning algorithms and is known for its ability to handle complex decision boundaries and high-dimensional data. At its core, SVM aims to find an optimal hyperplane in the feature space that best separates the data into different classes. The hyperplane is determined by selecting a subset of training samples called support vectors, which are the data points closest to the decision boundary.

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