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https://en.wikipedia.org/wiki/Support-vector_machine
In machine learning, support-vector machines (SVMs, also support-vector networks) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis.Given a set of training examples, each marked as belonging to one or the other of two categories, an SVM training algorithm builds a model that assigns new examples to one category ...
https://www.coursera.org/lecture/machine-learning/using-an-svm-sKQoJ
Video created by Stanford University for the course "Machine Learning". Support vector machines, or SVMs, is a machine learning algorithm for classification. We introduce the idea and intuitions behind SVMs and discuss how to use it in practice.
https://www.datasciencelearner.com/hyperparameters-for-the-support-vector-machines/
If you have earlier build the machine learning model using a support vector machine, then this tutorial is for you. You will learn how to optimize your model accuracy using the SVM() parameters. In this intuition, you will know how to find the best hyperparameters for …
https://www.coursera.org/lecture/machine-learning/kernels-i-YOMHn
Video created by Stanford University for the course "Machine Learning". Support vector machines, or SVMs, is a machine learning algorithm for classification. We introduce the idea and intuitions behind SVMs and discuss how to use it in practice.
https://link.springer.com/chapter/10.1007%2F978-3-662-47926-1_26
Aug 09, 2015 · Abstract. Support Vector Machine (SVM) is one of the fastest growing methods of machine learning due to its good generalization ability and good convergence performance; it has been successfully applied in various fields, such as text classification, statistics, pattern recognition, and …Cited by: 7
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