SVM-KA layer block
The SVM-KA block is a Support Vector Machine Kernel Adatron classifer.
Support Vector Machines (SVMs) are a powerful type of classifiers that can solve very complex classification problems. They can to that better than any other algorithm currently known to mankind, but it comes at a serious cost: SVMs are one of the most resource demanding adaptive algorithms available as well. They scale badly with data size and evaluation of a trained system is extremely slow as well.
The Synapse SVM component is a variety called a Kernel Adatron, which is a binary classification algorithm. It is reasonably fast as far as SVMs go, but it is limited to solving binary classification problems ( problems that only include two classes).
The component has two ports, one (top) that takes the input signal and the other (bottom) that takes the desired classification. The desired classification must be on ordinal (one feature with values -1 or 1) or nominal (two features with values [1 -1] or [-1 1] form.
The settings can be modified using the settings browser.
|SVM-KA Layer settings|
The SVM-KA has a standard basic interface:
- Block - Article covering general block principles.
- List of Block components - List of all available blocks.