Learning with Support Vector Machines

Häftad, Engelska, 2011

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Support Vectors Machines have become a well established tool within machine learning. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise.

Produktinformation

Utgivningsdatum2011-02-10
Mått191 x 235 x 6 mm
Vikt197 g
FormatHäftad
SpråkEngelska
SerieSynthesis Lectures on Artificial Intelligence and Machine Learning
Antal sidor83
FörlagSpringer International Publishing AG
ISBN9783031004247
OriginaltitelLearning with Support Vector Machines

Tillhör följande kategorier

Tillämpad matematik inom Naturvetenskap och teknik
Systemvetenskap och AI inom Data och IT
Artificiell intelligens inom Data och IT

Dr. Colin Campbell holds a BSc degree in physics from Imperial College, London, and a PhD in mathematics from King's College, London. He joined the Faculty of Engineering at the University of Bristol in 1990 where he is currently a Reader. His main interests are in machine learning and algorithm design. Current topics of interest include kernel-based methods, probabilistic graphical models and the application of machine learning techniques to medical decision support and bioinformatics. His research is supported by the EPSRC, Cancer Research UK, the MRC and PASCAL2. Dr. Yiming Ying received his BSc degree in mathematics from Zhejiang University (formally, Hangzhou University) in 1997 and his PhD degree in mathematics from Zhejiang University in 2002, Hangzhou, China. He is currently a Lecturer (Assistant Professor) in Computer Science in the College of Engineering, Mathematics and Physical Sciences at the University of Exeter, UK. His research interests include machine learning, pattern analysis, convex optimization, probabilistic graphical models and applications to bioinformatics and computer vision.

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