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Support Vector Machines (SVMs) are a type of supervised machine learning algorithm used in data mining and predictive analytics. SVMs are used to classify data into two or more categories, and to identify patterns and trends in data. SVMs are based on the concept of finding a hyperplane that best divides a dataset into two classes, and can be used for both classification and regression tasks. SVMs are also used for non-linear classification, and can be used to identify outliers in a dataset.
SVMs are widely used in a variety of industries, including finance, healthcare, and retail. They are used to identify customer segments, detect fraud, and predict customer behavior. SVMs are also used in natural language processing, image recognition, and bioinformatics.
Some companies in the SVM market include IBM, Microsoft, Google, Amazon, and Oracle. Show Less Read more