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https://en.wikipedia.org/wiki/Structured_support_vector_machine
The structured support vector machine is a machine learning algorithm that generalizes the Support Vector Machine (SVM) classifier. Whereas the SVM classifier supports binary classification, multiclass classification and regression, the structured SVM allows training of a …
https://en.wikipedia.org/wiki/Category:Support_vector_machines
Pages in category "Support vector machines" The following 9 pages are in this category, out of 9 total. This list may not reflect recent changes ().
https://en.wikipedia.org/wiki/Least-squares_support-vector_machine
Least-squares support-vector machines (LS-SVM) are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis.
https://en.wikipedia.org/wiki/Regularization_perspectives_on_support_vector_machines
Regularization perspectives on support-vector machines provide a way of interpreting support-vector machines (SVMs) in the context of other machine-learning algorithms. SVM algorithms categorize multidimensional data, with the goal of fitting the training set data well, but also avoiding overfitting, so that the solution generalizes to new data points. ...
https://en.wikipedia.org/wiki/Talk:Support-vector_machine
Support-vector machine is within the scope of WikiProject Robotics, which aims to build a comprehensive and detailed guide to Robotics on Wikipedia. If you would like to participate, you can choose to edit this article , or visit the project page ( Talk ), …
https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47
Jun 07, 2018 · Support vector machine is another simple algorithm that every machine learning expert should have in his/her arsenal. Support vector machine is highly preferred by many as it produces significant accuracy with less computation power. Support Vector Machine, abbreviated as SVM can be used for both regression and classification tasks.Author: Rohith Gandhi
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