Open Source Java Machine Learning Software - Page 7

The Elasticsearch Learning to Rank plugin uses machine learning to improve search relevance ranking. It's powering search at places like Wikimedia Foundation and Snagajob.

Exchange-core is an open-source market exchange core based on LMAX Disruptor, Eclipse Collections (ex. Goldman Sachs GS Collections), Real Logic Agrona, OpenHFT Chronicle-Wire, LZ4 Java, and Adaptive Radix Trees. Designed for high scalability and pauseless 24/7 operation under high-load conditions and providing low-latency responses. Single order book configuration is capable to process 5M operations per second on 10-years old hardware (Intel® Xeon® X5690) with moderate latency degradation. HFT optimized. Priority is a limit-order-move operation mean latency (currently ~0.5µs). Cancel operation takes ~0.7µs, placing new order ~1.0µs. Disk journaling and journal replay support, state snapshots (serialization) and restore operations, LZ4 compression. Lock-free and contention-free order matching and risk control algorithms. Matching engine and risk control operations are atomic and deterministic.

Moved to https://github.com/quansun/fantail-ml

feed4weka is an open library that enriches weka (http://www.cs.waikato.ac.nz/ml/weka/), an open source project for data analysis. It integrates new classification and clustering algorithms, and adds the coclustering and outlier detection frameworks

Feature Graphs Miner

A general purpose Finite State Machine written in Java. It is easy to use, powerful, and fast.

We moved to GitHub: https://github.com/grobid/grobid

An information extraction library implementing modern algorithms for the extraction of named entities from text.

jFAN2 project develops a Java API to use a neural network (neuro-fuzzy) called FAN (Free Associative Neurons). Its an reprogramed version of jFAN "https://sourceforge.net/projects/jfan/".

The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/

Open project ternary classifier of the machine learning

libVMR is a class library written in Java which implements code generator for group method of data handling - GMDH. The library is intended for users, with machine learning skills. libVMR provides an effective framework for the research and development of data mining and predictive analytics. libVMR is based on the most popular neural network model with a higher generalization ability from kernel tricks - vector machine by Reshetov (VMR). The library has been designed to learn from data sets. Typical applications here are pattern recognition ( binary classification).

Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.

This Java software implements Profile Hidden Markov Models (PHMMs) for protein classification for the WEKA workbench. Standard PHMMs and newly introduced binary PHMMs are used. In addition the software allows propositionalisation of PHMMs.

Rastreie.me Mestrado Profissional em Computação Aplicada UTFPR Dissertação de Mestrado Jean Pierobom jean@pierobom.com

weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.

Extensible framework that enables productive design, analysis, and execution of arbitrary-sized neural-networks or system on a distributed, scalable, high-throughput runtime platform. Enables synapse-oriented-programming.