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WEKA

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  Analyzed 1 day ago

Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is ... [More] also well-suited for developing new machine learning schemes. [Less]

780K lines of code

3 current contributors

over 1 year since last commit

38 users on Open Hub

Very Low Activity
3.93333
   
0 Reviews
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Mostly written in Java
Licenses: No declared licenses
Tags algorithms analysis api artificial_intelligence association_mining association_rules business_intelligence classifiers clustering data data_analysis data_mining 13 more...

YALE Open-Source Java Data Mining

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  Analyzed about 14 hours ago

YALE (Yet Another Learning Environment) is the most comprehensive open-source software for intelligent data analysis, data mining, knowledge discovery, machine learning, predictive analytics, forecasting, and analytics in business intelligence (BI). YALE provides more than 400 data mining operators ... [More] , a graphical user interface (GUI), an online tutorial with hands-on data mining applications, a comprehensive PDF tutorial, many visualization schemes for data sets and data mining results, many different learning and meta-learning schemes ranging from decision tree and rule learners to neural networks, SVMs, ensemble methods, etc. YALE is implemented in Java and available under GPL (GNU General Public License) as well as under a developer license (OEM license) for closed-source developers. [Less]

751K lines of code

0 current contributors

over 9 years since last commit

17 users on Open Hub

Inactive
4.25
   
0 Reviews
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Mostly written in Java
Licenses: No declared licenses
Tags analysis data data_analysis data_mining development education framework intelligent_data_analysis java java_data_mining kdd knowledge_discovery 5 more...

Java Data Mining Package (JDMP)

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  Analyzed 1 day ago

The Java Data Mining Package (JDMP) is an open source Java library for data analysis and machine learning. It facilitates the access to data sources and machine learning algorithms (e.g. clustering, regression, classification, graphical models, optimization) and provides visualization modules. It ... [More] includes a matrix library for storing and processing any kind of data, with the ability to handle very large matrices even when they do not fit into memory. Import and export interfaces are provided for JDBC data bases, TXT, CSV, Excel, Matlab, Latex, MTX, HTML, WAV, BMP and other file formats. JDMP provides a number of algorithms and tools, but also interfaces to other machine learning and data mining packages (Weka, LibSVM, Mallet, Lucene, Octave). [Less]

40.7K lines of code

0 current contributors

over 8 years since last commit

2 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Java
Licenses: lgpl3
Tags algorithms analysis artificial_intelligence classification classifiers clustering data data_analysis data_mining distributed intelligent_data_analysis java 11 more...

Java Machine Learning Library

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  Analyzed about 22 hours ago

The Java Machine Learning Library is a set of reference implementations of machine learning algorithms. These algorithms are well documented, both in the source code as on the documentation site. Besides real machine learning algorithms also a lot of supporting classes are provided: distance ... [More] measures, evaluation criteria, datasets for validation purposes and some sample code. Currently the library contains clustering algorithms, distance measures, wavelet transforms, fourier transforms, matrices, support vector machines and some other algorithms [Less]

19.9K lines of code

0 current contributors

about 11 years since last commit

1 users on Open Hub

Inactive
5.0
 
0 Reviews
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Mostly written in Java
Licenses: gpl
Tags algorithms api classifiers data_mining java knowledge_discovery library machine_learning research science

ELKI

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  Analyzed about 4 hours ago

ELKI: "Environment for Developing KDD-Applications Supported by Index-Structures" is a development framework for data mining algorithms written in Java. It includes a large variety of popular data mining algorithms, distance functions and index structures. Its focus is particularly on clustering ... [More] and outlier detection methods, in contrast to many other data mining toolkits that focus on classification. Additionally, it includes support for index structures to improve algorithm performance such as R*-Tree and M-Tree. The modular architecture is meant to allow adding custom components such as distance functions or algorithms, while being able to reuse the other parts for evaluation. [Less]

214K lines of code

2 current contributors

9 days since last commit

1 users on Open Hub

Moderate Activity
5.0
 
0 Reviews
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Mostly written in Java
Licenses: AGPL3_or_...
Tags algorithms analysis api clustering data data_analysis data_mining datamining dataminingframework java kdd knowledge_discovery 8 more...