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Software developed at LS8

Several progams have been and are developed in parallel to our research activity. Most of them are actively maintained by their author.
TitelDescriptionAuthor(s)Related projectsID
Structural Support Vector MachineImplements the SVMstruct in Java Pfahler, Lukas
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Kernmengenbasiertes Clustering auf Streams efkpcwrzeo
Subspace Clustering ExtensionRapidMiner Extension for Subspace Clustering with frequent items Skirzynski, Marcin
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YALE Clustering Plugin (now fully integrated in RapidMiner)A plugin that provides a framework and some basic functionality to enable advanced clustering in YALE (since YALE/RapidMiner 4.0 fully integrated into the YALE/RapidMiner 4.0 core) Wurst, Michael
AWAKE
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kXMLkXML 2 is a small XML pull parser, specially designed for constrained environments such as Applets, Personal Java or MIDP devices. Haustein, Stefan
COMRIS
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Information LayerCOMRIS Information Layer Haustein, Stefan
COMRIS
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MiningMart system Euler, Timm
Scholz, Martin
MiningMart
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PicanaPicana 2.0 is an algorithm for the Farthest-Pairs-Problem. Stolpe, Marco
SFB 475 subproject A4
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mySVM/dbmySVM/db is a Java re-implementation mySVM. It is designed to run directly inside a database system. Rüping, Stefan
SFB 475 subproject A4
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myKLRA software for kernel logistic regression Rüping, Stefan
SFB 475 subproject A4
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SVM-lightAn implementation of Support Vector Machines in C Joachims, Thorsten
SFB 475 subproject A4
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RapidMiner Value Series Plugin(Automatic) Feature extraction from value series with RapidMiner (formerly YALE) Mierswa, Ingo
SFB 475 subproject A4
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UschificatorScaling of classifier membership values Rüping, Stefan
SFB 475 subproject A4
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RapidMiner Data Stream Plugin (formerly: YALE Concept Drift Plugin)Extension of RapidMiner (formerly YALE) for machine learning and data mining from time-varying data streams and for tracking drifting concepts Klinkenberg, Ralf
SFB 475 subproject A4
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mySVMmySVM is an implementation of the Support Vector Machine introduced by V. Vapni. It is based on the optimization algorithm of SVM-light. mySVM can be used for pattern recognition, regression and distribution estimation. Rüping, Stefan
SFB 475 subproject A4
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RapidMiner (YALE)RapidMiner (formerly YALE) is an integrated environment for machine learning, data mining, and knowledge discovery experiments and applications Fischer, Simon
Klinkenberg, Ralf
Mierswa, Ingo
SFB 475 subproject A4
SFB 531 Computational Intelligence
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rsig: Robust Signature Selection for Survival Outcomes Lee, Sangkyun
SFB 876
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LLPThe LLP-Plugin for RapidMiner contains operators for learning from label proportions. Stolpe, Marco
SFB 876
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HHHPluginHierarchical Heavy Hitter plugin for RapidMiner 5. Fricke, Peter
Stolpe, Marco
SFB 876
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PRIMP and PANPALBoolean matrix factorization with automatic rank determination. Hess, Sibylle
Piatkowski, Nico
SFB 876
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Deconvolution algorithms for Cherenkov astronomy Bunse, Mirko
SFB 876
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Optimization Plugin for RapidMinerThe optimization plugin for RapidMiner aims to introduce mathematical optimization based learning capability. Umaashankar, Venkatesh
SFB 876
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RapidMiner Microarray Feature Selection PluginOperators for feature selection and classificationof high-dimensional (microarray-) data Schowe, Benjamin
Sivakumar, Viswanath
SFB 876
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