Support Vector Machines (SVMs) are some of the most performant off-the-shelf, supervised machine-learning algorithms. In Support Vector Machines Succinctly, author Alexandre Kowalczyk guides readers through the building blocks of SVMs, from basic concepts to crucial problem-solving algorithms. He also includes numerous code examples and a lengthy bibliography for further study. By the end of the book, SVMs should be an important tool in the reader’s machine-learning toolbox.
Prerequisites
The Perceptron
The SVM Optimization Problem
Solving the Optimization Problem
Soft Margin SVM
Kernels
The SMO Algorithm
Multi-Class SVMs
Conclusion
Appendix A: Datasets
Appendix B: The SMO Algorithm
978-1-64200-150-1
October 23, 2017
114
Looking for something specific? Try our title or author search.
