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Knowledge Discovery with Support Vector Machines

Perceptron learning Maximum margin classifiers Support vector machines Elements of statistical learning theory Multi-class classification;

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Support Vector Machines and Their Application in Chemistry and Biotechnology

Elements and algorithms of support vector classification (SVC) and support vector regression (SVR) machines, along with discussion of simulated;

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Support Vector Machines and Their Application in Chemistry and Biotechnology

Elements and algorithms of support vector classification (SVC) and support vector regression (SVR) machines, along with discussion of simulated;

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Regularization, Optimization, Kernels, and Support Vector Machines

in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso Discusses;

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Regularization, Optimization, Kernels, and Support Vector Machines

in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso;

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Learning with Support Vector Machines

from multiple types of input data. Table of Contents: Support Vector Machines for Classification / Kernel-based Models / Learning with;

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Support Vector Machines

This book presents topical research in the study of support vector machines. Topics discussed include the support vector machine in medical;

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Twin Support Vector Machines

This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments;

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Twin Support Vector Machines

This book provides a systematic and focused study of the various aspects of twin support vector machines (TWSVM) and related developments;

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Learning with Support Vector Machines

Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used;

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Machine Learning and Visual Perception

learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design;

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Sequence Classification Using Support Vector Machines

explained. After that an introduction in classification tasks, machine learning and support vector machines will be given and the so called Motif;

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Support Vector Machines

Support Vector Machines: Optimization Based Theory, Algorithms, and Extensions presents an accessible treatment of the two main components;

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Gentle Introduction To Support Vector Machines In Biomedicine, A - Volume 2

Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning;

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Gentle Introduction To Support Vector Machines In Biomedicine, A - Volume 1

Support Vector Machines (SVMs) are among the most important recent developments in pattern recognition and statistical machine learning;

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Machine Learning

of Support Vector Machines. To provide a next stage of development, the book finishes with a discussion on SVM kernels as a way and motivation to;

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Introduction Support Vector Machines

This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances;

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Interpretability of Computational Intelligence Based Regression Models

The key idea of this book is that hinging hyperplanes, neural networks and support vector machines can be transformed into fuzzy models;

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Machine Learning: A Practical Approach on the Statistical Learning Theory

motivations for the Support Vector Machines. From that, we introduce all necessary optimization concepts related to the implementation of Support;

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Introduction To Pattern Recognition And Machine Learning

networks, support vector machines and decision trees - attributed to the recent vast progress in this field are also dealt with. Introduction to;

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Mathematics for Machine Learning

central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For;

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Mathematics for Machine Learning

central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For;

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Support Vector Machines

of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety;

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Support Vector Machines

of this book is to explain the principles that made support vector machines (SVMs) a successful modeling and prediction tool for a variety;

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An Introduction to Machine Learning

-neighbor classifiers, linear and polynomial classifiers, decision trees, neural networks, and support vector machines. Later chapters show how to;

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Support Vector Machines for Antenna Array Processing and Electromagnetics

Support Vector Machines (SVM) were introduced in the early 90's as a novel nonlinear solution for classification and regression tasks;

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Support Vector Machines for Antenna Array Processing And Electromagnetics

Support Vector Machines (SVM) were introduced in the early 90's as a novel nonlinear solution for classification and regression tasks;

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