Searching for Knowledge Discovery With Support Vector Machines information? Find all needed info by using official links provided below.
https://www.amazon.com/Knowledge-Discovery-Support-Vector-Machines/dp/0470371927
Jan 02, 2012 · Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are pursuing research in machine learning and related areas.Cited by: 254
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470503065
Jul 20, 2009 · Regression with support vector machines. Novelty detection. Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses. It is also an excellent tutorial on support vector machines for professionals who are ...
https://www.amazon.com/Knowledge-Discovery-Support-Vector-Machines/product-reviews/0470371927
Find helpful customer reviews and review ratings for Knowledge Discovery with Support Vector Machines at Amazon.com. Read honest and unbiased product reviews from our users.4.8/5(8)
https://link.springer.com/article/10.1023%2FA%3A1009715923555
Abstract. The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail.Cited by: 21017
https://www.sciencedirect.com/science/article/pii/S016516841400574X
Multi-task support vector machines for feature selection with shared knowledge discovery. ... O. Chapelle, S.S. Keerthi, Multi-class feature selection with support vector machines, in: Proceedings of the American Statistical Association, 2008.Cited by: 31
https://www.bookdepository.com/Knowledge-Discovery-with-Support-Vector-Machines-Lutz-H-Hamel/9780470371923
Aug 03, 2009 · Support vector machines Elements of statistical learning theory Multi-class classification Regression with support vector machines Novelty detection Complemented with hands-on exercises, algorithm descriptions, and data sets, Knowledge Discovery with Support Vector Machines is an invaluable textbook for advanced undergraduate and graduate courses.4.2/5(10)
https://www.di.ens.fr/~mallat/papiers/svmtutorial.pdf
Keywords: Support Vector Machines, Statistical Learning Theory, VC Dimension, Pattern Recognition Appeared in: Data Mining and Knowledge Discovery 2, 121-167, 1998 1. Introduction The purpose of this paper is to provide an introductory yet extensive tutorial on the basic ideas behind Support Vector Machines (SVMs). The books (Vapnik, 1995 ...
https://onlinelibrary.wiley.com/doi/pdf/10.1002/9780470503065.ch7
Summary This chapter contains sections titled: The Lagrangian Dual Dual Maximum‐Margin Optimization Linear Support Vector Machines Nonlinear Support Vector Machines Soft‐Margin Classifiers Tool Sup...
https://www.microsoft.com/en-us/research/publication/a-tutorial-on-support-vector-machines-for-pattern-recognition/
The tutorial starts with an overview of the concepts of VC dimension and structural risk minimization. We then describe linear Support Vector Machines (SVMs) for separable and non-separable data, working through a non-trivial example in detail. We describe a mechanical analogy, and discuss when SVM solutions are unique and when they are global.Cited by: 21017
How to find Knowledge Discovery With Support Vector Machines information?
Follow the instuctions below:
- Choose an official link provided above.
- Click on it.
- Find company email address & contact them via email
- Find company phone & make a call.
- Find company address & visit their office.
