Transductive Support Vector Machines

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On Transductive Support Vector Machines - Statistics

    http://users.stat.umn.edu/~xshen/paper/tsvm.pdf
    transductive support vector machine (TSVM; Vapnik, 1998), which remains mysterious, particularly its “al-leged” unstable performance in empirical studies. TSVM seeks the largest separation between labeled and unlabeled data through regularization. In em-pirical studies, it performs well in text classification

Transductive SVMs

    http://www.cs.cmu.edu/~guestrin/Class/10701-S06/Slides/tsvms-pca.pdf
    Transductive support vector machines (TSVMs) w. x ... transductive SVMs What is transductive v. semi-supervised learning Formulation for transductive SVM can also be used for semi-supervised learning Optimization is hard! Integer program There are simple heuristic solution methods that

What are the Transductive Support Vector Machines (TSVMs ...

    https://www.quora.com/What-are-the-Transductive-Support-Vector-Machines-TSVMs
    The objective function for regular SVM maximizes the margin, alongwith the constraints that positive datapoints and negative datapoints are on opposite sides of the separating hyperplane. The regular SVM formulation can use only labeled datapoints...

(PDF) On Transductive Support Vector Machines

    https://www.researchgate.net/publication/250884384_On_Transductive_Support_Vector_Machines
    Transductive support vector machines (TSVM) has been widely used as a means of treating partially labeled data in semi- supervised learning. Around it, there has been mystery because of …

Large-scale robust transductive support vector machines ...

    https://www.sciencedirect.com/science/article/pii/S0925231217300292
    In this paper, we propose a robust and fast transductive support vector machine (RTSVM) classifier that can be applied to large-scale data. To this end, we use the robust Ramp loss instead of Hinge loss for labeled data samples.Cited by: 6

Learning with progressive transductive support vector machine

    https://www.sciencedirect.com/science/article/pii/S0167865503000084
    Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead of an inductive one in support vector classifiers, the working set can be used as an additional source of information about margins.Cited by: 188

Transductive Support Vector Machines (TSVM) - Python ...

    https://subscription.packtpub.com/book/big_data_and_business_intelligence/9781789957211/2/ch02lvl1sec17/transductive-support-vector-machines-tsvm
    Transductive Support Vector Machines (TSVM) Another approach to the same problem is offered by the TSVM, proposed by T. Joachims (in Transductive Inference for Text Classification using Support Vector Machines, Joachims T., ICML Vol. 99/1999). The idea is to keep the original objective with two sets of slack variables: the first for the labeled ...

Machine Learning with Missing Labels: Transductive SVMs

    https://calculatedcontent.com/2014/09/23/machine-learning-with-missing-labels-transductive-svms/
    Sep 23, 2014 · Machine Learning with Missing Labels: Transductive SVMs. September 23, 2014 Charles H Martin, PhD Uncategorized 15 comments. SVMs are great for building text classifiers–if you have a set of very high quality, labeled documents. ... W. Pan On Transductive Support Vector Machines [9] ...

[PDF] Transductive Inference for Text Classification using ...

    https://www.semanticscholar.org/paper/Transductive-Inference-for-Text-Classification-Joachims/74b1a9e50f18af8a7b9f8dd38f40e0466ad7a8e8
    This paper introduces Transductive Support Vector Machines (TSVMs) for text classi cation. While regular Support Vector Machines (SVMs) try to induce a general decision function for a learning task, Transductive Support Vector Machines take into account a particular test set and try to minimize misclassi cations of just those particular examples.



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