Twin Support Vector Machines for Pattern Classification

By Jayadeva, Reshma Khemchandani, Suresh Chandra. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007

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Data Mining for the Internet of Things: Literature Review and Challenges (2015, methodology): “GSVM (granular support vector machines) [42-44], FSVM (fuzzy support vector machines) [45-47], TWSVMs ((twin support vector machines) [48-50], VaR-SVM (Value-at-risk support vector machines) [51], RSVM (ranking support vector machines) [52].”
Improvements on Twin Support Vector Machines (2011, methodology): “For binary classification, an improved version of TBSVM based on the TWSVM in [8] was proposed in this brief.”
TSVR: An efficient Twin Support Vector Machine for regression (2010, methodology): “Similar to TSVM (Jayadeva et al., 2007), TSVR also solves two smaller sized quadratic programming problems (QPPs) instead of solving large one as in a classical SVR.”
Robust twin support vector machine for pattern classification (2013, methodology): “This can improve the model’s generalized capability efficiently [14,13,39].”