Support Vector Machines for Pattern Classification - Shigeo Abe
-20% with code BOOKS
Shipping in 12-18 days
30-day return policy
A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ab ... Full description
You May Also Like
TOP
The Design of Everyday Things
-20% with code BOOKS
In stock at our supplier
TOP
If Anyone Builds It, Everyone Dies: The Case Against Superintelligent AI
Eliezer Yudkowsky, Nate Soares
-20% with code BOOKS
In stock at our supplier
TOP
We Are Not Machines: The Fight for the Future of Work
-20% with code BOOKS
In stock at our supplier
TOP
Open Circuits: The Inner Beauty of Electronic Components
Eric Schlaepfer, Windell Oskay
-20% with code BOOKS
In stock at our supplier
TOP
Get started with MicroPython on Raspberry Pi Pico: The Official Raspberry Pi Pico Guide
-20% with code BOOKS
In stock at our supplier
TOP
Practical Electronics for Inventors
-20% with code BOOKS
In stock at our supplier
TOP
Fundamentals of Aerodynamics ISE
Christopher Cadou, John D. Anderson
-20% with code BOOKS
In stock at our supplier
TOP
Nucleo Boards Programming with the STM32CubeIDE: Hands-on in more than 50 projects
-20% with code BOOKS
In stock at our supplier
TOP
Black Holes: The Key to Understanding the Universe
-20% with code BOOKS
In stock at our supplier
TOP
KiCad Like A Pro - Fundamentals and Projects: Getting started with the world's best open-source PCB tool
-20% with code BOOKS
In stock at our supplier
TOP
Make: Electronics: Learning by Discovery: A hands-on primer for the new electronics enthusiast
-20% with code BOOKS
In stock at our supplier
TOP
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
Steven L. Brunton, J. Nathan Kutz
-20% with code BOOKS
In stock at our supplier
TOP
Flowers For Algernon: A Modern Literary Classic
-20% with code BOOKS
In stock at our supplier
TOP
Foundations of Flavor: The Noma Guide to Fermentation: Including Step-By-Step Information on Making and Cooking with: Koji, Kombuchas, Shoyus, Misos, Vinegars, Garums, Lacto-Ferments and black Fruits Vegetables
-20% with code BOOKS
In stock at our supplier
TOP
Professional SMD Assembly: Practical Low-Cost Methods for Reliable PCB Production
-20% with code BOOKS
In stock at our supplier
TOP
Digital Design and Computer Architecture, RISC-V Edition
-20% with code BOOKS
In stock at our supplier
TOP
Blood in the Machine: The Origins of the Rebellion Against Big Tech
-20% with code BOOKS
In stock at our supplier
TOP
Mastering the Arduino Uno R4: Programming and Projects for the Minima and WiFi
-20% with code BOOKS
In stock at our supplier
TOP
Collection of Exercises for PLC Programming: 100 programming exercises from beginner to expert level
-20% with code BOOKS
In stock at our supplier
Description
A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empirical feature space, and the effect of model selection by cross-validation; Covers sparse SVMs, learning using privileged information, semi-supervised learning, multiple classifier systems, and multiple kernel learning; Explores incremental training based batch training and active-set training methods, and decomposition techniques for linear programming SVMs; Discusses variable selection for support vector regressors.
More Information
| Author | Shigeo Abe |
|---|---|
| Publisher | Springer London |
| Release year | 2012 |
| Cover type | Softcover |
| EAN | 9781447125488 |