Project details for ADAMS

Screenshot ADAMS 0.4.10

by fracpete - June 22, 2015, 23:14:58 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

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Description:

The Advanced Data mining and Machine learning System, or short ADAMS, is a novel, flexible workflow engine aimed at quickly building and maintaining real-world, complex knowledge workflows. Instead of placing operators on a canvas and manually connecting them, a tree structure and flow control operators determine how the data is being processed, e.g., sequentially or in parallel. This approach allows the rapid development and easy maintenance of large workflows, consisting of hundreds or even thousands of operators. ADAMS offers operators for machine learning libraries like WEKA and MOA and image processing libraries such as ImageJ, Java Advanced Imaging (JAI), ImageMagick and Gnuplot. Via Rserve, the R-Project can be incorporated in flows for data processing. With the WEKA webservice, other frameworks can take advantage of WEKA's models as well. For fast prototyping the user can use scripting languages such as Groovy and Jython. GIS support is possible with the OpenStreetMap integration.

Changes to previous version:
  • fixes a glitch in the debugging functionality, when using the Breakpoint control actor
BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Agnostic
Data Formats: Arff, Csv, Tab Separated, Libsvm, Xrff, Excel, Odf, Xls, Xlsx
Tags: R, Workflow, Weka, Image Processing, Webservice, Moa, Gis, Openstreetmap, Meka
Archive: download here

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