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https://www.sciencedirect.com/science/article/pii/S0030401812002453
Jun 15, 2012 · According to the principle of support vector machine (SVM) and the inter-class separability rule of hyperspectral data, a novel binary tree SVM classifier based on separability measure among different classes is proposed for hyperspectral image classification.Cited by: 29
https://en.wikipedia.org/wiki/Support-vector_machine
Support-vector machine weights have also been used to interpret SVM models in the past. Posthoc interpretation of support-vector machine models in order to identify features used by the model to make predictions is a relatively new area of research with special significance in the biological sciences. History
https://www.researchgate.net/profile/Soo-Young_Lee2/publication/229006003_Support_vector_machines_with_binary_tree_architecture_for_multi-class_classification/links/53f1f9380cf2bc0c40e6f3f3.pdf
Figure 1. Support Vector Machines with Binary Tree Architecture (SVM-BTA) for the classification of 10 classes from “0” to “9”. The overlaps are allowed for the classes “5” and “7”. 2.
https://www.researchgate.net/publication/229006003_Support_vector_machines_with_binary_tree_architecture_for_multi-class_classification
A complete framework of binary tree of support vector machine based on posterior probability (PPBTSVM) is proposed by introducing soft labels into the enhanced binary tree of SVM (c-BTS).
https://www.mathworks.com/help/stats/support-vector-machines-for-binary-classification.html
Support Vector Machines for Binary Classification Understanding Support Vector Machines. Separable Data. Nonseparable Data. Nonlinear Transformation with Kernels. Separable Data. You can use a support vector machine (SVM) when your data has exactly two classes. An SVM classifies data by finding the best hyperplane that separates all data points ...
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