A efficient implementation of the Sequential Minimal Optimization (SMO) algorithm for training Support Vector Machines (SVMs). Exposes training and prediction in a side-effect free, functional programming style.
To use in your own project, add the following to your build.sbt:
libraryDependencies += "io.malcolmgreaves" %% "smo-fun" % "X.Y.Z"
Where X.Y.Z is the latest version (check the maven central badge in this README).
This repository is split into subprojects:
-
- contains algorithm implementations
- intended to be consumed as a library
-
- contains command line applications that use the code from
smo-fun-core - intended to be used as a suite of tools to assist fellow machine learniner practitioners
- contains command line applications that use the code from
Only the smo-fun-core project adheres to the published version semantics.
The original author (Malcolm Greaves) retains copyright over all material contained within this repository. [1] Use of this code is governed under the terms of the Apache 2.0 open source software license. See the LICENSE file for more details.
[1] Excludes content from the data/ directory as most of this was obtained from free and open sources on the internet (inclding the wonderful UCI ML Repository!).