###### regression

- More formally, a support vector machine constructs a hyperplane or set of hyperplanes in a high- or infinite-dimensional space, which can be used for classification , regression , or other tasks like outliers detection. (wikipedia.org)
- SVM light is an implementation of Vapnik's Support Vector Machine [ Vapnik, 1995 ] for the problem of pattern recognition, for the problem of regression, and for the problem of learning a ranking function. (cornell.edu)
- Machine learning of swimming data via wisdom of crowd and regression analysis. (aimsciences.org)
- Gunn SR (1998) Support vector machines for classification and regression. (springer.com)

###### classification

- Based on the collected proteins, we developed a carbohydrate-binding protein prediction system by using machine learning methods, with which predicting carbohydrate-binding proteins can be formulated as a binary classification problem. (hindawi.com)
- Support vector machine (SVM) is a very popular method for binary data classification in data mining (machine learning). (aimsciences.org)
- The major features were submitted to a kernel support vector machine (KSVM) for performing the MRI classification. (springer.com)
- Recent research efforts to improve the reliability and accuracy of image classification have led to the introduction of the Support Vector Classification (SVC) scheme. (springer.com)
- Foody GM, Mathur A (2004) A relative evaluation of multiclass image classification by support vector machines. (springer.com)
- Huang C, Davis LS, Townshed JRG (2002) An assessment of support vector machines for land cover classification. (springer.com)
- Hsu CW, Chang CC, Lin CJ (2003) A practical guide to support vector classification. (springer.com)
- In addition, a new fitness function, which combines the classification accuracy obtained from bootstrap method, the number of chosen features, and the number of support vectors, is proposed to lead the search of CGPGA to the direction of optimal generalization error. (hindawi.com)
- C.W. Hsu, C.C. Chang and C.J. Lin: A Practical Guide to Support Vector Classification, Department of Computer Science and Information Engineering National Taiwan University. (scientific.net)

###### quadratic surface support

- Fuzzy quadratic surface support vector machine based on fisher discriminant analysis. (aimsciences.org)
- More importantly, our method is based on the state-of-the-art non-kernel fuzzy quadratic surface support vector machine (FQSSVM) model which not only performs superiorly in prediction, but also becomes very applicable to the users. (aimsciences.org)

###### optimization

- Application of support vector machine model in wind power prediction based on particle swarm optimization. (aimsciences.org)
- On fractional vector optimization over cones with support functions. (aimsciences.org)
- Subgradient-based neural network for nonconvex optimization problems in support vector machines with indefinite kernels. (aimsciences.org)
- H. Chew and C. Lim , On regularisation parameter transformation of support vector machines, Journal of Industrial and Management Optimization , 5 (2009), 403-415. (aimsciences.org)

###### Multiclass

- Übeyli, E.D.: Multiclass support vector machines for diagnosis of erythemato-squamous diseases. (springer.com)
- Performance evaluation of multiobjective multiclass support vector machines maximizing geometric margins. (aimsciences.org)

###### neural

- Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (coursera.org)
- While the model based on support vector machine (SVM) and BP neural network can identify cracks of supported beam intelligently, the methods can discern injured degrees of sound condition, single crack, and double cracks. (hindawi.com)
- Kecman, V.: Learning and Soft Computing, Support Vector machines, Neural Networks and Fuzzy Logic Models. (springer.com)
- Abstract: This paper investigates the short-term wind power forecasting and demonstrates accurate modeling, which utilizes two representative heuristic algorithms (i.e. wavelet neural network (WNN) and Multilayer Perceptron (MLP)), and statistical machine learning techniques (i.e. (scientific.net)

###### Fuzzy

- Wang, T.Y., Chiang, H.M.: Fuzzy support vector machine for multi-class text categorization. (springer.com)

###### Shawe-Taylor

- Cristianini, N., Shawe-Taylor, J.: An introduction to support vector machines and other kernel-based learning methods. (springer.com)

###### 2001

- In order to overcome this model's non-smooth property, Lee and Mangasarian proposed smooth support vector machine (SSVM) in 2001. (aimsciences.org)
- C. C. Chang and C. J. Lin, "LIBSVM: a library for support vector machines," 2001. (hindawi.com)

###### orthogonal

- The hyperplanes in the higher-dimensional space are defined as the set of points whose dot product with a vector in that space is constant, where such a set of vector is an orthogonal (and thus minimal) set of vectors that defines a hyperplane. (wikipedia.org)

###### predictor

- Multiple measures are defined to quantify the domain information content of each position along the sequence and are combined into a single predictor using support vector machines. (springer.com)

###### Kernel

- Advances in Kernel Methods - Support Vector Learning, B. Sch lkopf and C. Burges and A. Smola (ed. (cornell.edu)
- Keerthi SS, Lin CJ (2003) Asymptotic behaviors of support vector machines with Gaussian kernel. (springer.com)

###### method

- The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM). (hindawi.com)
- Home Applied Mechanics and Materials e-Engineering & Digital Enterprise Technology Support Vector Machine-Based Method for Quality. (scientific.net)

###### speech recognition

- In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. (coursera.org)

###### bankruptcy

- U. Dellepiane , M. Marcantonio , E. Laghi and S. Renzi , Bankruptcy prediction using support vector machines and feature selection during the recent financial crisis, International Journal of Economics and Finance , 7 (2015), 182-194. (aimsciences.org)

###### artificial intelligence

- In this way, recent works on artificial intelligence techniques have led to introduce a robust machine learning methodology called support vector machine. (hindawi.com)

###### optimal

- Optimal parameter selection in support vector machines. (aimsciences.org)

###### application

- Support Vector Machines: Theory and Application. (springer.com)

###### statistical

- This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. (coursera.org)
- Statistical discrimination of steroid profiles in doping control with support vector machines. (nih.gov)

###### aims

- Uplift modeling is a branch of machine learning which aims to predict not the class itself, but the difference between the class variable behavior in two groups: treatment and control. (springer.com)
- This paper aims at designing an calibration technique for temperature measurement using support vector machine. (springer.com)

###### Learning

- Classifying data is a common task in machine learning . (wikipedia.org)
- Machine learning is the science of getting computers to act without being explicitly programmed. (coursera.org)
- Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. (coursera.org)
- In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. (coursera.org)
- Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. (coursera.org)
- innovation process in machine learning and AI). (coursera.org)
- It is often difficult and time-consuming to develop classifiers by hand, so many researchers have turned to techniques from the fields of statistics and machine learning to automatically generate classifiers. (osti.gov)

###### tasks

- Many tasks have the property of sparse instance vectors. (cornell.edu)

###### image

- Lu Yang, Gongping Yang, Yilong Yin , Rongyang Xiao, "Finger vein image quality evaluation using support vector machines," Optical Engineering 52(2), 027003 (18 February 2013). (spiedigitallibrary.org)

###### Keywords

- These keywords were added by machine and not by the authors. (springer.com)

###### chosen

- Meanwhile, the sensitive feature vectors are randomly chosen from the database and constitute training samples and testing samples. (hindawi.com)

###### evaluation

- In an extensive empirical evaluation OCAS significantly outperforms current state of the art SVM solvers, like SVMLight, SVMPerf and BMRM, achieving speedups of over 1,000 on some datasets over SVMLight and 20 over SVMPerf, while obtaining the same precise Support Vector solution. (videolectures.net)

###### time

- Kim, K.J.: Financial time series forecasting using support vector machines. (springer.com)

###### solution

- Canonical duality solution for alternating support vector machine. (aimsciences.org)

###### software

- Elish, K.O., Elish, M.O.: Predicting defect-prone software modules using support vector machines. (springer.com)

###### fields

- Support theorem for the Light-Ray transform of vector fields on Minkowski spaces. (aimsciences.org)