Support Vector Machines: Theory and Applications
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Beschreibung
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in the respective fields.
The support vector machine (SVM) has become one of the standard tools for machine learning and data mining. This carefully edited volume presents the state of the art of the mathematical foundation of SVM in statistical learning theory, as well as novel algorithms and applications. Support Vector Machines provides a selection of numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection, written by leading experts in their respective fields.
Carefully edited volume presenting the state of the art of Support Vector Machines Presents theory, algorithms and applications Includes numerous real-world applications, such as bioinformatics, text categorization, pattern recognition, and object detection
Autor*in
Lipo Wang
Themen in »Support Vector Machines: Theory and Applications«
Data Mining Fuzzy Kernel Machines Pattern Recognition Soft Computing Statistical Learning algorithm algorithms bioinformatics cognition learning learning theory machine learning model proving