IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v24y2009i2p303-311.html
   My bibliography  Save this article

How to talk to strangers: ways to leverage connectivity between R, Java and Objective C

Author

Listed:
  • Simon Urbanek

Abstract

No abstract is available for this item.

Suggested Citation

  • Simon Urbanek, 2009. "How to talk to strangers: ways to leverage connectivity between R, Java and Objective C," Computational Statistics, Springer, vol. 24(2), pages 303-311, May.
  • Handle: RePEc:spr:compst:v:24:y:2009:i:2:p:303-311
    DOI: 10.1007/s00180-008-0132-x
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00180-008-0132-x
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s00180-008-0132-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kurt Hornik & Christian Buchta & Achim Zeileis, 2009. "Open-source machine learning: R meets Weka," Computational Statistics, Springer, vol. 24(2), pages 225-232, May.
    2. Theus, Martin, 2002. "Interactive Data Visualization using Mondrian," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 7(i11).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Souhila Ghanem & Raphaël Couturier & Pablo Gregori, 2021. "An Accurate and Easy to Interpret Binary Classifier Based on Association Rules Using Implication Intensity and Majority Vote," Mathematics, MDPI, vol. 9(12), pages 1-12, June.
    2. Grubinger, Thomas & Zeileis, Achim & Pfeiffer, Karl-Peter, 2014. "evtree: Evolutionary Learning of Globally Optimal Classification and Regression Trees in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i01).
    3. Mariane S. Reis & Maria Isabel S. Escada & Luciano V. Dutra & Sidnei J. S. Sant’Anna & Nathan D. Vogt, 2018. "Towards a Reproducible LULC Hierarchical Class Legend for Use in the Southwest of Pará State, Brazil: A Comparison with Remote Sensing Data-Driven Hierarchies," Land, MDPI, vol. 7(2), pages 1-29, May.
    4. Matthias Templ & Andreas Alfons & Peter Filzmoser, 2012. "Exploring incomplete data using visualization techniques," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 6(1), pages 29-47, April.
    5. John W. Emerson, 2008. "Interactive and Dynamic Graphics for Data Analysis: With R and GGobi by COOK, D. and SWAYNE, D," Biometrics, The International Biometric Society, vol. 64(4), pages 1301-1303, December.
    6. Tomokazu Fujino, 2007. "SVG+Ajax+R: a new framework for WebGIS," Computational Statistics, Springer, vol. 22(4), pages 511-520, December.
    7. Rashid Mehmood & Muhammad Riaz & Ronald Does, 2013. "Efficient power computation for r out of m runs rules schemes," Computational Statistics, Springer, vol. 28(2), pages 667-681, April.
    8. Stefano Castellana & Caterina Fusilli & Gianluigi Mazzoccoli & Tommaso Biagini & Daniele Capocefalo & Massimo Carella & Angelo Luigi Vescovi & Tommaso Mazza, 2017. "High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-12, June.
    9. Maria Janicka & Bogumiła Pawluśkiewicz & Tomasz Gnatowski, 2023. "Preliminary Results of the Introduction of Dicotyledonous Meadow Species," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    10. Fabian Meyer-Brötz & Edgar Schiebel & Leo Brecht, 2017. "Experimental evaluation of parameter settings in calculation of hybrid similarities: effects of first- and second-order similarity, edge cutting, and weighting factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1307-1325, June.
    11. Chi-Chang Chang & Tse-Hung Huang & Pei-Wei Shueng & Ssu-Han Chen & Chun-Chia Chen & Chi-Jie Lu & Yi-Ju Tseng, 2021. "Developing a Stacked Ensemble-Based Classification Scheme to Predict Second Primary Cancers in Head and Neck Cancer Survivors," IJERPH, MDPI, vol. 18(23), pages 1-10, November.
    12. C. Hurley & R. Oldford, 2011. "Eulerian tour algorithms for data visualization and the PairViz package," Computational Statistics, Springer, vol. 26(4), pages 613-633, December.
    13. Ana D. Maldonado & Darío Ramos-López & Pedro A. Aguilera, 2018. "A Comparison of Machine-Learning Methods to Select Socioeconomic Indicators in Cultural Landscapes," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    14. Gustavo Cattelan Nobre & Elaine Tavares, 2017. "Scientific literature analysis on big data and internet of things applications on circular economy: a bibliometric study," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 463-492, April.
    15. Bogdan Oancea, 2023. "Automatic Product Classification Using Supervised Machine Learning Algorithms in Price Statistics," Mathematics, MDPI, vol. 11(7), pages 1-32, March.
    16. David Fernández-Nogueira & Eduardo Corbelle-Rico, 2019. "Determinants of Land Use/Cover Change in the Iberian Peninsula (1990–2012) at Municipal Level," Land, MDPI, vol. 9(1), pages 1-12, December.
    17. Kumasaka, Natsuhiko & Shibata, Ritei, 2008. "High-dimensional data visualisation: The textile plot," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3616-3644, March.
    18. Hao-Yun Kao & Chi-Chang Chang & Chin-Fang Chang & Ying-Chen Chen & Chalong Cheewakriangkrai & Ya-Ling Tu, 2022. "Associations between Sex and Risk Factors for Predicting Chronic Kidney Disease," IJERPH, MDPI, vol. 19(3), pages 1-11, January.
    19. Nai-Hua Chen, 2020. "Exploring the Cognitive and Emotional Impact of Online Climate Change Videos on Viewers," Sustainability, MDPI, vol. 12(22), pages 1-16, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:compst:v:24:y:2009:i:2:p:303-311. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.