KNIME

KNIME - Professional Open-Source Software. KNIME is a user-friendly graphical workbench for the entire analysis process: data access, data transformation, initial investigation, powerful predictive analytics, visualisation and reporting. The open integration platform provides over 1000 modules (nodes), including those of the KNIME community and its extensive partner network. KNIME can be downloaded onto the desktop and used free of charge. KNIME products include additional functionalities such as shared repositories, authentication, remote execution, scheduling, SOA integration and a web user interface as well as world-class support. Robust big data extensions are available for distributed frameworks such as Hadoop. KNIME is used by over 3000 organizations in more than 60 countries.


References in zbMATH (referenced in 12 articles )

Showing results 1 to 12 of 12.
Sorted by year (citations)

  1. Curtis T. Rueden, Johannes Schindelin, Mark C. Hiner, Barry E. DeZonia, Alison E. Walter, Kevin W. Eliceiri: ImageJ2: ImageJ for the next generation of scientific image data (2017) arXiv
  2. Hu, Qiwei; Chakhar, Salem; Siraj, Sajid; Labib, Ashraf: Spare parts classification in industrial manufacturing using the dominance-based rough set approach (2017)
  3. Ralf Mikut, Andreas Bartschat, Wolfgang Doneit, Jorge Angel Gonzalez Ordiano, Benjamin Schott, Johannes Stegmaier, Simon Waczowicz, Markus Reischl: The MATLAB Toolbox SciXMiner: User’s Manual and Programmer’s Guide (2017) arXiv
  4. Bernatavičienė, Jolita; Dzemyda, Gintautas; Kurasova, Olga; Marcinkevičius, Virginijus; Medvedev, Viktor; Treigys, Povilas: Cloud computing approach for intelligent visualization of multidimensional data (2016)
  5. Nascimento, Susana: Applying the gradient projection method to a model of proportional membership for fuzzy cluster analysis (2016)
  6. Fournier-Viger, Philippe; Gomariz, Antonio; Gueniche, Ted; Soltani, Azadeh; Wu, Cheng-Wei; Tseng, Vincent S.: SPMF: a Java open-source pattern mining library (2014)
  7. Madeyski, Lech; Majchrzak, Marek: Software measurement and defect prediction with DePress extensible framework (2014) ioport
  8. Piccolo, Stephen R.; Frey, Lewis J.: ML-flex: a flexible toolbox for performing classification analyses in parallel (2012)
  9. Berthold, Michael R; Borgelt, Christian; Höppner, Frank; Klawonn, Frank: Guide to intelligent data analysis. How to intelligently make sense of real data (2010)
  10. Alcalá-Fdez, J.; Sánchez, L.; García, S.; del Jesus, M.J.; Ventura, S.; Garrell, J.M.; Otero, J.; Romero, C.; Bacardit, J.; Rivas, V.M.; Fernández, J.C.; Herrera, F.: KEEL: a software tool to assess evolutionary algorithms for data mining problems (2009) ioport
  11. Berthold, Michael R.; Cebron, Nicolas; Dill, Fabian; Gabriel, Thomas R.; Kötter, Tobias; Meinl, Thorsten; Ohl, Peter; Thiel, Kilian; Wiswedel, Bernd: KNIME - the Konstanz information miner: version 2.0 and beyond (2009) ioport
  12. Tiwari, Abhishek; Sekhar, Arvind K.T.: Workflow based framework for life science informatics (2007)