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https://www.techopedia.com/definition/30364/support-vector-machine-svm
A support vector machine (SVM) is machine learning algorithm that analyzes data for classification and regression analysis. SVM is a supervised learning method that looks at data and sorts it into one of two categories. An SVM outputs a map of the sorted data with the margins between the two as far apart as possible.
https://whatis.techtarget.com/definition/support-vector-machine-SVM
A support vector machine (SVM) is a type of deep learning algorithm that performs supervised learning for classification or regression of data groups. In AI and machine learning, supervised learning systems provide both input and desired output data, which are labeled for classification.
https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47
Jun 07, 2018 · Support Vector Machine, abbreviated as SVM can be used for both regression and classification tasks. But, it is widely used in classification objectives. What is Support Vector Machine? The objective of the support vector machine algorithm is to find a hyperplane in an N-dimensional space(N — the number of features) that distinctly classifies ...
https://www.saedsayad.com/support_vector_machine.htm
A Support Vector Machine (SVM) performs classification by finding the hyperplane that maximizes the margin between the two classes. The vectors (cases) that define the hyperplane are the support vectors. Algorithm: Define an optimal hyperplane: maximize margin; Extend the above definition for non-linearly separable problems: have a penalty term ...
https://docs.opencv.org/2.4/doc/tutorials/ml/introduction_to_svm/introduction_to_svm.html
A Support Vector Machine (SVM) is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data (supervised learning), the algorithm outputs an optimal hyperplane which categorizes new examples.
https://towardsdatascience.com/support-vector-machines-for-classification-fc7c1565e3
Jul 07, 2019 · Support Vector Machines are a very powerful machine learning model. Whereas we focused our attention mainly on SVMs for binary classification, we can extend their use to multiclass scenarios by using techniques such as one-vs-one or one-vs-all, which would involve the creation of one SVM for each pair of classes.
http://cs229.stanford.edu/notes/cs229-notes3.pdf
Support Vector Machines This set of notes presents the Support Vector Machine (SVM) learning al-gorithm. SVMs are among the best (and many believe are indeed the best) “off-the-shelf” supervised learning algorithms. To tell the SVM story, we’ll need to first talk about margins and the idea of separating data with a large “gap.”
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