Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
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TLDR
Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.Abstract:
LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM to their applications. LIBSVM has gained wide popularity in machine learning and many other areas. In this article, we present all implementation details of LIBSVM. Issues such as solving SVM optimization problems theoretical convergence multiclass classification probability estimates and parameter selection are discussed in detail.read more
Citations
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Revealing the physics of movement: Comparing the similarity of movement characteristics of different types of moving objects
TL;DR: The method can be employed in classifying trajectory data generated by unknown moving objects and assigning them to known types of moving objects, whose movement characteristics have been previously learned and can be successfully applied in automatic transport mode detection.
Journal ArticleDOI
Coregulation of Transcription Factor Binding and Nucleosome Occupancy through DNA Features of Mammalian Enhancers
Iros Barozzi,Marta Simonatto,Silvia Bonifacio,Lin Yang,Remo Rohs,Serena Ghisletti,Gioacchino Natoli +6 more
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Wendy Liu,Derek Ruths +1 more
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Spontaneous facial micro-expression analysis using Spatiotemporal Completed Local Quantized Patterns
TL;DR: Wang et al. as discussed by the authors proposed spatiotemporal completed local quantization patterns (STCLQP) for facial micro-expression analysis. But, their method only considers appearance and motion features from the sign-based difference between two pixels but not yet considers other useful information.
Journal ArticleDOI
Feature Extraction and Selection for Myoelectric Control Based on Wearable EMG Sensors.
TL;DR: From these results, two new sets of recommended EMG features (along with a novel feature, L-scale) are identified that provide better performance for these emerging low-sampling rate systems.
References
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Journal ArticleDOI
Support-Vector Networks
Corinna Cortes,Vladimir Vapnik +1 more
TL;DR: High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated and the performance of the support- vector network is compared to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.
Statistical learning theory
TL;DR: Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.
Proceedings ArticleDOI
A training algorithm for optimal margin classifiers
TL;DR: A training algorithm that maximizes the margin between the training patterns and the decision boundary is presented, applicable to a wide variety of the classification functions, including Perceptrons, polynomials, and Radial Basis Functions.
A Practical Guide to Support Vector Classication
TL;DR: A simple procedure is proposed, which usually gives reasonable results and is suitable for beginners who are not familiar with SVM.
Journal ArticleDOI
A comparison of methods for multiclass support vector machines
Hsu Chih-Wei,Chih-Jen Lin +1 more
TL;DR: Decomposition implementations for two "all-together" multiclass SVM methods are given and it is shown that for large problems methods by considering all data at once in general need fewer support vectors.