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Apache Mahout

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Claimed by Apache Software Foundation Analyzed 3 days ago

Apache Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. ... [More] However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms [Less]

146K lines of code

0 current contributors

10 months since last commit

25 users on Open Hub

Very Low Activity
3.6
   
0 Reviews
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Mostly written in Java
Licenses: apache_2
Tags algorithms classifiers clustering collaborative_filtering data_mining datamining dimension_reduction distributed distributed_computing hadoop java library 5 more...

SpagoBI

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Claimed by The OW2 Consortium No analysis available

SpagoBI is an integration platform focused on business intelligence needs at the enterprise level. It's a full open source solution, no professional edition. SpagoBI offers a complete analytical layer : reporting ,OLAP, data mining, dashboards, free and visual data inquiring, GIS. It is built on a ... [More] flexible SOA architecture and portal approach allowing user to customize their own workspace. [Less]

0 lines of code

0 current contributors

0 since last commit

9 users on Open Hub

Activity Not Available
5.0
 
0 Reviews
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Mostly written in language not available
Licenses: mozilla_p...
Tags bi dashbord datamart datamining datawarehouse gis olap qbe reporting

lava-server

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Claimed by Linaro No analysis available

Linaro Automated Validation Architecture server, including lava-scheduler and lava-dashboard.

0 lines of code

32 current contributors

0 since last commit

4 users on Open Hub

Activity Not Available
5.0
 
0 Reviews
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Mostly written in language not available
Licenses: AGPL3
Tags arm automation bootloader continuous_integration datamining django graphing ipxe lava linaro linaro_lava linux 8 more...

Crab - Scikit-Recommender

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  Analyzed 3 days ago

Crab is a flexible, fast recommender engine for Python that integrates classic information filtering recommendation algorithms in the world of scientific Python packages (NumPy,SciPy, Matplotlib). The engine aims to provide a rich set of components from which you can construct a customized ... [More] recommender system from a set of algorithms. It is designed for scability, flexibility and performance making use of scientific optimized python packages in order to provide simple and efficient solutions that are acessible to everybody and reusable in various contexts: science and engineering. [Less]

4.21K lines of code

0 current contributors

over 12 years since last commit

2 users on Open Hub

Inactive
5.0
 
0 Reviews
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Mostly written in Python
Licenses: BSD-3-Clause
Tags ai algorithms collaborative_filtering collectiveintelligence data_mining datamining distributed evaluation library machine_learning machinelearning plugable 8 more...

SOFA Statistics

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  Analyzed about 11 hours ago

SOFA is a statistics, analysis, and reporting program with an emphasis on ease of use, learn as you go, and beautiful output.

37K lines of code

0 current contributors

2 months since last commit

1 users on Open Hub

Very Low Activity
0.0
 
0 Reviews
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Mostly written in Python
Licenses: No declared licenses
Tags database datamining python reporting statisticalanalysis statistics

Sally Tool

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  Analyzed 1 day ago

Sally is a small tool for mapping a set of strings to a set of vectors. This mapping is referred to as embedding and allows for applying techniques of machine learning and data mining for analysis of string data. Sally implements a standard technique for mapping strings to a vector space that is ... [More] often referred to as vector space model or bag-of-words model. The strings are characterized by a set of features, where each feature is associated with one dimension of the vector space. Sally proceeds by counting the occurrences of the specified features in each string and generating a sparse vector of count values. The tool then normalizes the vectors and outputs them in a given format. [Less]

5.62K lines of code

1 current contributors

over 5 years since last commit

1 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in C
Licenses: gpl3
Tags datamining machinelearning strings vectorspace

jMotif

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  Analyzed about 9 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

almost 3 years since last commit

1 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Java
Licenses: gpl
Tags anomaly_detection behavior_analysis clustering datamining distance java kdd metrics paa patterns sax search 5 more...

refine-client-py

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  Analyzed about 10 hours ago

The Google Refine Python Client Library provides an interface to communicating with a Google Refine server.

1.41K lines of code

0 current contributors

about 10 years since last commit

1 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Python
Licenses: No declared licenses
Tags datamining etl gridworks python python27 refine

Knowing Datamining

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  Analyzed 2 days ago

Datamining framework based on WEKA and Akka.

8.58K lines of code

0 current contributors

over 10 years since last commit

1 users on Open Hub

Inactive
0.0
 
0 Reviews
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Mostly written in Scala
Licenses: apache_2
Tags data datamining eclipse fault-tolerance faulttolerance fault-tolerant framework java modular osgi scala weka

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]

215K lines of code

2 current contributors

22 days since last commit

1 users on Open Hub

Very Low 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...