Journal ArticleDOI
LIBSVM: A library for support vector machines
Chih-Chung Chang,Chih-Jen Lin +1 more
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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Journal ArticleDOI
Comparison of Classification Algorithms and Training Sample Sizes in Urban Land Classification with Landsat Thematic Mapper Imagery
TL;DR: In this paper, the spectral information provided by the Landsat Thematic Mapper (TM) data set and the same classification scheme over Guangzhou City, China, was tested with two unsupervised and 13 supervised classification algorithms, including a number of machine learning algorithms.
Journal ArticleDOI
Genomic regions flanking E-box binding sites influence DNA binding specificity of bHLH transcription factors through DNA shape
TL;DR: Custom protein-binding microarrays are used to analyze TF specificity for putative binding sites in their genomic sequence context and suggest that nucleotides outside E-box binding sites contribute to specificity by influencing the three-dimensional structure of DNA binding sites.
Proceedings ArticleDOI
BodyScope: a wearable acoustic sensor for activity recognition
Koji Yatani,Khai N. Truong +1 more
TL;DR: A wearable acoustic sensor, called BodyScope, is developed to record the sounds produced in the user's throat area and classify them into user activities, such as eating, drinking, speaking, laughing, and coughing.
Journal ArticleDOI
Does feature selection improve classification accuracy? Impact of sample size and feature selection on classification using anatomical magnetic resonance images.
TL;DR: It is shown that the most accurate characterizations are achieved by using prior knowledge of where to expect neurodegeneration (hippocampus and parahippocampal gyrus) and that feature selection does improve the classification accuracies, but it depends on the method adopted.
Journal ArticleDOI
Limited options for low-global-warming-potential refrigerants
TL;DR: It is shown that only a few pure fluids possess the combination of chemical, environmental, thermodynamic, and safety properties necessary for a refrigerant and that these fluids are at least slightly flammable.
References
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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
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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.