malcolmgreaves / smo-fun

An efficient implementation of the Sequential Minimal Optimization algorithm for training SVMs.

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smo-fun

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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).

Project Structure

This repository is split into subprojects:

  • smo-fun-core

    • contains algorithm implementations
    • intended to be consumed as a library

  • smo-fun-cmd

    • 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

Versioning

Only the smo-fun-core project adheres to the published version semantics.

Legal

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!).

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[![smo-fun Scala version support](https://index.scala-lang.org/malcolmgreaves/smo-fun/smo-fun/latest-by-scala-version.svg)](https://index.scala-lang.org/malcolmgreaves/smo-fun/smo-fun)
libraryDependencies += "io.malcolmgreaves" %% "smo-fun" % "0.0.0"
Ammonite REPL 
import $ivy.`io.malcolmgreaves::smo-fun:0.0.0`
<dependency>
  <groupId>io.malcolmgreaves</groupId>
  <artifactId>smo-fun_2.11</artifactId>
  <version>0.0.0</version>
</dependency>
compile group: 'io.malcolmgreaves', name: 'smo-fun_2.11', version: '0.0.0'
Mill build tool 
ivy"io.malcolmgreaves::smo-fun:0.0.0"
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