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AI-algorithms

A collection of well-known AI and machine learning algorithms

License

License
GroupId

GroupId

com.github.bentorfs
ArtifactId

ArtifactId

ai-algorithms
Last Version

Last Version

0.2.0
Release Date

Release Date
Type

Type

jar
Description

Description

AI-algorithms
A collection of well-known AI and machine learning algorithms
Project URL

Project URL

https://github.com/bentorfs/AI-algorithms
Source Code Management

Source Code Management

https://github.com/bentorfs/AI-algorithms.git

Download ai-algorithms

Filename Size
ai-algorithms-0.2.0.pom
ai-algorithms-0.2.0.jar 37 KB
ai-algorithms-0.2.0-sources.jar 20 KB
ai-algorithms-0.2.0-javadoc.jar 197 KB
Browse

How to add to project

<!-- https://jarcasting.com/artifacts/com.github.bentorfs/ai-algorithms/ -->
<dependency>
    <groupId>com.github.bentorfs</groupId>
    <artifactId>ai-algorithms</artifactId>
    <version>0.2.0</version>
</dependency>
// https://jarcasting.com/artifacts/com.github.bentorfs/ai-algorithms/
implementation 'com.github.bentorfs:ai-algorithms:0.2.0'
// https://jarcasting.com/artifacts/com.github.bentorfs/ai-algorithms/
implementation ("com.github.bentorfs:ai-algorithms:0.2.0")
'com.github.bentorfs:ai-algorithms:jar:0.2.0'
<dependency org="com.github.bentorfs" name="ai-algorithms" rev="0.2.0">
  <artifact name="ai-algorithms" type="jar" />
</dependency>
@Grapes(
@Grab(group='com.github.bentorfs', module='ai-algorithms', version='0.2.0')
)
libraryDependencies += "com.github.bentorfs" % "ai-algorithms" % "0.2.0"
[com.github.bentorfs/ai-algorithms "0.2.0"]

Dependencies

compile (2)

Group / Artifact Type Version
org.slf4j : slf4j-log4j12 jar 1.7.5
org.apache.commons : commons-math3 jar 3.2

test (3)

Group / Artifact Type Version
junit : junit jar 4.10
joda-time : joda-time jar 2.3
commons-lang : commons-lang jar 2.6

Project Modules

There are no modules declared in this project.

AI-algorithms

A selection of well-known AI and machine learning algorithms, implemented in Java. The code is very domain-agnostic, so it can be adapted for many tasks. The goal is to create a lightweight library for quick prototyping and simple production applications. If you really have a lot of data, you should use Apache Mahout.

Many of the ML algorithms were taken from the great bible of Machine Learning - Tom M. Mitchell

Usage

To see an example of how to use the library, take a look at the unit tests. One or more applications are included for each one.

Maven

<dependency>
    <groupId>com.github.bentorfs</groupId>
    <artifactId>ai-algorithms</artifactId>
    <version>0.2.0</version>
</dependency>

Included algorithms

Data Mining

  • Agglomerative hierarchical clustering
  • Association rules: apriori

Artificial Neural Networks

  • Perceptron training using perceptron rule or stochastic gradient descent
  • Multi-layer feedforward networks
  • Sigmoid units
  • Backpropagation

Reinforcement learning

  • Q-learning, using
  • Boltzmann action selection
  • Є-greedy action selection

Graph algorithms

  • A* search

Game playing algorithms

  • Minimax
  • Alpha-beta pruning

Versions

Version
0.2.0
0.1.0