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WEKA

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  Analyzed about 19 hours 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

almost 2 years since last commit

38 users on Open Hub

Very Low Activity
3.93333
   
I Use This
Licenses: No declared licenses

YALE Open-Source Java Data Mining

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  Analyzed 1 day 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
   
I Use This
Licenses: No declared licenses

jMotif

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  Analyzed about 12 hours ago

JMotif implements in Java number of methods for timeseries data handling and analysis: * Z normalization of timeseries * Piecewise Aggregate Approximation (PAA) of timeseries * Symbolic Aggregate Approximation (SAX) of timeseries * iSAX (indexed SAX) in order to help one leverage the symbolic ... [More] representation of timeseries, it implements: * TFIDF statistics * Cosine similarity * Sequitur algorithm as well as their application for: * Motif (recurring patterns) detection with SAX * Discord (unique patterns) detection with SAX * Timeseries classification * Timeseries clustering [Less]

4.3K lines of code

0 current contributors

over 2 years since last commit

1 users on Open Hub

Inactive
0.0
 
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ELKI

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  Analyzed 1 day 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

27 days since last commit

1 users on Open Hub

Moderate Activity
5.0
 
I Use This