In this work, we developed classifiers to distinguish between four ovarian tumor types using Bayesian least squares support vector machines (LS-SVMs) and kernel logistic regression...
Ben Van Calster, Dirk Timmerman, Antonia C. Testa,...
Margin maximizing properties play an important role in the analysis of classi£cation models, such as boosting and support vector machines. Margin maximization is theoretically in...
In this paper, we use the previously proposed calibrated DCT features [9] to construct a Support Vector Machine classifier for JPEG images capable of recognizing which steganograp...
This paper explores the scalability issues associated with solving the Named Entity Recognition (NER) problem using Support Vector Machines (SVM) and high-dimensional features and ...
When linear support vector machines (SVMs) are applied to multi-class text categorization in industry, the size of the linear SVM model is very large, usually greater than several...