Open Source Java Algorithms

Java Machine Learning Library is a library of machine learning algorithms and related datasets. Machine learning techniques include: clustering, classification, feature selection, regression, data pre-processing, ensemble learning, voting, ...

This library contains Java code for several Read-Write Locks: - ScalableRWLock: A rw-lock that scales with the number of threads doing read-lock. - ScalableRWLockS: Similar to above but different implementation. - ScalableStampedRWLock: An hybrid of the ScalableRWLock and the StampedLock provided in JDK 8, which provides good overall performance. - FAARWLock: Uses a Fetch-And-Add operation for the read-lock which means it is not so scalable as ScalableRWLock but it is still faster than classical implementations

DisChoco is a Distributed Constraint Reasoning Solver. Several Distributed Constraint Reasoning algorithms are implemented (like ABT, AFC, Adopt, ...). Users may easily implement and test their algorithms with DisChoco. contact: wahbi[at]users[dot]sourceforge[dot]net

SDD: Duplicated code detection tool

a sandbox for trying my engine ideas

ADiV is a set of components for LAMW that uses JAVA and Pascal. It stands out for the simplicity of programming, thanks to the use of Pascal and hiding the Java Android code.

Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.

The Aim of this project is to provide a collection of reusable Algorithms which can be used effectively in different scenarios. Algorithm implementations are in Java. Objective here is to implement algorithms which should be more efficient than the JDK implementation and also to create a platform for the researchers who works on Data Mining, Encryption algorithms, ect.. to collaborate and contribute to this project.

The goal: to provide implementations of as many algorithms (sorting, searching, ...) and data structures (lists, trees, ...) as possible, accompanied by discussion of big O run time and memory limits and references to sources of further study.

The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.

Toolbox for Java developers. Includes right now only a multi-layered extensible cache system but will grow depending on requirements.

Bebops ("Belief Base Operations") provides semi-revision, contraction and kernel operators for an OWL-backed Belief Base.

This is a Java-based project for complex event extraction from text and co-reference resolution. Currently the code can read BioNLP shared task format (http://2011.bionlp-st.org/) and i2b2 Natural Language Processing for Clinical Data shared task format (https://www.i2b2.org/NLP/DataSets/Main.php). Event extraction includes finding events and the parameters for an event in a text. The method is based on SVM but other ML algorithms can be adopted. The method details are explained in the following paper: Ehsan Emadzadeh, Azadeh Nikfarjam, and Graciela Gonzalez. 2011. Double Layered Learning for Biological Event Extraction from Text. In Proceedings of the BioNLP 2011 Workshop Companion Volume for Shared Task, Portland, Oregon, June. Association for Computational Linguistic

Bricks4J is a set of common tools, utils and classes for Java, aiming to ease development for a widespread kind of tasks.

CSGraph is a simple graph library. It provides the most popular algorithms to create and manipulate graphs.

Combean is a Java framework for mathematical structures and optimization algorithms. Through a set of Java interfaces and JavaBeans-based config, Combean glues optimization codes together - leading to more interoperable, adaptable and flexible solutions.

Project provides a set of concurrent building blocks (Java & C/C++) that can be used to develop parallel/multi-threaded applications. Components are grouped into 4 categories: 1.Data Structures 2. Parallel Patterns 3.Parallel functions 4.Atomics and STM

Cutting Problem solved by Genetic algorithms. The goal is to cut a rectangular plate of material into more smaller rectangles. The cuts must be rectangular and guillotinable.

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments demonstrate that the proposed method performs promisingly for well-known benchmark problems in the term of optimization accuracy.

FUMOLA is a co-simulation framework specifically designed to support the features offered by the FMI specification. It provides a flexible platform that allows to configure and execute co-simulation setups in an easy way. FUMOLA is developed on top of the Ptolemy II framework (https://ptolemy.eecs.berkeley.edu) and the FMI++ library (http://fmipp.sourceforge.net). The online documentation of FUMOLA is available here: https://sourceforge.net/p/fumola/wiki/Home/

Provide geneology information, contact information, personal descriptions and webpages, calendars, etc in a web interface. This system will use php and any database system and will provide various level of public and private access.

Ocean with fishes who's are learning and evolving.

FORce based Cluster Editing (FORCE) is a Java software heuristically solving the graph cluster editing problem on weighted edges using BLAST E-values. It further provides a training mode for heuristic parameter estimation.

Galapagos is a Genetic Algorithm framework written in Java 5 with the intended audience of undergraduates in an Artificial Intelligence class. The goal of Galapagos is usability: a competent student should be able to learn this library in an afternoon.

GeneThello (read jə-ˈne-ˈthe-lō), is an acronym for genetic othello, an othello (reversi) playing program which based on Genetic Algorithm (GA). In principle GeneThello consist of an othello program and a genetic algorithm system.