Weighted Margin Support Vector Machine

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Weighted K-means support vector machine for cancer prediction

    https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960100/
    In this paper, I propose the weighted K-means support vector machine (wKM-SVM) and weighted support vector machine (wSVM), for which I allow the SVM to impose weights to the loss term. Besides, I demonstrate the numerical relations between the objective function of the SVM and weights.Cited by: 9

Weighted Linear Support Vector Machine DataScience+

    https://datascienceplus.com/weighted-linear-support-vector-machine/
    Apr 06, 2017 · Notice that the proportion of spam and ham in the training data set is similar to that of the entire data. One of the widely used classifiers is Linear Support Vector Machine. From my last writing on Linear Support Vector Machine, you can find that in case of Linear SVM we solve the following optimization problem.Author: Ananda Das

Distance-weighted Support Vector Machine - arXiv

    https://arxiv.org/pdf/1310.3003.pdf
    method is named Distance-weighted Support Vector Machine (DWSVM) to salute the above two classical methods. As shown in Panel (d) of Figure1, DWSVM preserves a good direction by showing the Gaussian pattern in the projections while nds a good intercept term which is …

A Weighted Least Squares Twin Support Vector Machine

    https://www.iis.sinica.edu.tw/page/jise/2014/201411_06.pdf
    Least squares twin support vector machine (LS-TSVM) aims at resolving a pair of smaller-sized quadratic programming problems (QPPs) instead of a single large one as in the conventional least squares support vector machine (LS-SVM), which makes the learning speed of LS-TSVM faster than that of LS-SVM. However, same penalties are

Incorporating prior knowledge with weighted margin support ...

    https://www.researchgate.net/publication/221653619_Incorporating_prior_knowledge_with_weighted_margin_support_vector_machines
    Weighted Margin Support Vector Machines (WMSVM) [49] is another way to solve the small-sampling problem by generalizing the original Support Vector Machines for incorporating prior knowledge. The ...

Find classification margins for support vector machine ...

    https://www.mathworks.com/help/stats/classificationsvm.resubmargin.html
    m = resubMargin(SVMModel) returns the resubstitution classification margins (m) for the support vector machine (SVM) classifier SVMModel using the training data stored in SVMModel.X and the corresponding class labels stored in SVMModel.Y.. m is returned as a numeric vector …

Learning SVM with weighted maximum margin criterion for ...

    https://www.sciencedirect.com/science/article/pii/S0895717710005315
    Learning SVM with weighted maximum margin criterion for classification of imbalanced data. ... whether the selected kernel matches the data determines the performance of support vector machine. Conventional support vector classifiers are not suitable to the imbalanced learning tasks since they tend to classify the instances to the majority ...Cited by: 22

A New Fuzzy Support Vector Machine Based on the Weighted ...

    https://link.springer.com/article/10.1007%2Fs11063-004-1640-5
    Nov 01, 2004 · The ideas from fuzzy neural networks and support vector machine (SVM) are incorporated to make SVM classifiers perform better. The influence of the samples with high uncertainty can be decreased by employing the fuzzy membership to weigh the margin of each training vector. The linear separability, fuzzy margin, optimal hyperplane, generalization and soft fuzzy margin algorithms …Cited by: 26

(PDF) Weighted support vector machine for data classification

    https://www.researchgate.net/publication/4202393_Weighted_support_vector_machine_for_data_classification
    This paper presents a weighted support vector machine (WSVM) to improve the outlier sensitivity problem of standard support vector machine (SVM) for two-class data classification.



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