Use support vector machines in JMSL
Support vector machines were implemented as part of the latest release of JMSL, along with expanded data mining functionality, including areas such as decision trees and bootstrap aggregation. The documentation of the IMSL Libraries is detailed and robust, but the algorithm discussion and examples can only cover a finite set of use cases.
This white paper will walk you through examples not covered in the documentation, with a focus on classification. We start with the textbook examples that are part of most SVM resources, providing notes and key points throughout.
Download this complimentary resource now, and receive access to a full code example which follows the examples outlined.