TABLE OF CONTENTS:
The Support Vector Machine (SVM) algorithm is a popular supervised machine learning algorithm that is widely used for classification and regression tasks. It is a powerful algorithm that is particularly useful when dealing with high-dimensional datasets. In this article, we will explore the SVM algorithm in detail and provide a step-by-step guide on how to implement it in Python.
The SVM algorithm is a binary classification algorithm that works by finding the hyperplane that best separates the data points of different classes. The hyperplane is chosen such that the margin between the hyperplane and the closest data points of each class is maximized. The closest data points to the hyperplane are called support vectors, hence the name Support Vector Machine.
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