Parameter selection is one of the important steps involved in any model fitting. In this paper we have used Uniform Design Tables to choose the parameters for PSVM and SVM to classify the data. UD is one of the efficient space filling designs, which spreads the combination of parameters in the space uniformly scattered and generalizes the performance of the model efficiently. This paper compare...

This paper is concerned with the optimization of the surface roughness when milling aluminium alloys (AA6061-T6) with carbide coated inserts. Optimization of milling is very useful to reduce cost and time for machining mould. Potential support vector machine (PSVM) is used to develop surface roughness predicted model. Design of experiments method and response surface methodology techniques are ...

In this paper, we have proposed a novel model called proximal support matrix machine (PSMM), which is mainly based on the models of vector (PSVM) and low rank (LRSMM). design, PSMM has comprehensively considered both relationship between samples same class structure rows or columns data. To certain extent, our can be regarded as synthesis PSVM LRSMM model. Since an unconstrained convex problem ...

PURPOSE We predict the likelihood of a future motor vehicle collision (MVC) from visual function data, attitudes to driving, and past MVC history using the penalized support vector machine (pSVM) in subjects with primary open-angle glaucoma (POAG). METHODS Patients with POAG were screened prospectively for eligibility and 185 were analyzed in this study. Self-reported MVCs of all participants...

Principal asymmetric least squares (PALS) is introduced as a novel method for sufficient dimension reduction with heteroscedastic error. Classical methods such MAVE [Xia et al. (2002), ‘An Adaptive Estimation of Dimension Reduction Space’ (with discussion), Journal the Royal Statistical Society Series B, 64, 363–410] and PSVM [Li (2011), ‘Principal Support Vector Machines Linear Nonlinear Suffi...

This paper proposes a simple model for speaker recognition based on i–vector pairs, and analyzes its similarity and differences with respect to the state–of–the–art Probabilistic Linear Discriminant Analysis (PLDA) and Pairwise Support Vector Machine (PSVM) models. Similar to the discriminative PSVM approach, we propose a generative model of i–vector pairs, rather than an usual i–vector based m...

Multi-view learning improves the performance of existing tasks by using complementary information between multiple feature sets. In latest research, multi-view model privileged is proposed; specific models are PSVM-2V and MCPK. these models, views complement each other acting as policies; however, a single view contains that can guide classifier, framework does not consider it. order to use thi...

In this document we first provide the derivation for incremental learning of PSVM parameters, which is used to update every decision node in our online Obli-RaF. Next, we provide a detailed analysis of various parameters of the proposed tracker, and demonstrate the merits of our Obli-RaF. Finally, we provide more detailed results of our approach on the OTB51, OTB-100 datasets and VOT2016 under ...