rattle: Graphical user interface for data mining in R , Rattle (the R Analytic Tool To Learn Easily) provides a Gnome (RGtk2) based interface to R functionality for data mining. The aim is to provide a simple and intuitive interface that allows a user to quickly load data from a CSV file (or via ODBC), transform and explore the data, build and evaluate models, and export models as PMML (predictive modelling markup language) or as scores. All of this with knowing little about R. All R commands are logged and commented through the log tab. Thus they are available to the user as a script file or as an aide for the user to learn R or to copy-and-paste directly into R itself. Rattle also exports a number of utility functions and the graphical user interface, invoked as rattle(), does not need to be run to deploy these. (Source: http://cran.r-project.org/web/packages)

References in zbMATH (referenced in 15 articles , 1 standard article )

Showing results 1 to 15 of 15.
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  1. Lux, Thomas C. H.; Watson, Layne T.; Chang, Tyler H.; Hong, Yili; Cameron, Kirk: Interpolation of sparse high-dimensional data (2021)
  2. Kalra, Meeta; Osadebey, Michael; Bouguila, Nizar; Pedersen, Marius; Fan, Wentao: Online variational learning for medical image data clustering (2020)
  3. He Zhao and Graham Williams and Joshua Huang: wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests (2017) not zbMATH
  4. Bischl, Bernd; Lang, Michel; Kotthoff, Lars; Schiffner, Julia; Richter, Jakob; Studerus, Erich; Casalicchio, Giuseppe; Jones, Zachary M.: mlr: machine learning in (\mathbfR) (2016)
  5. Dhhan, Waleed; Rana, Sohel; Midi, Habshah: Non-sparse (\varepsilon)-insensitive support vector regression for outlier detection (2015)
  6. Ifenthaler, Dirk; Widanapathirana, Chathuranga: Development and validation of a learning analytics framework: two case studies using support vector machines (2014) ioport
  7. Ledolter, Johannes: Data mining and business analytics with R (2013)
  8. Mwitondi, Kassim S.: Book review of: G. Williams, Data mining with Rattle and R (2013)
  9. Norman, Paul; Valentini, Paolo; Schwartzentruber, Thomas: GPU-accelerated Classical Trajectory Calculation Direct Simulation Monte Carlo applied to shock waves (2013)
  10. Ian Fellows: Deducer: A Data Analysis GUI for R (2012) not zbMATH
  11. Knisley, D.; Knisley, J.: Predicting protein-protein interactions using graph invariants and a neural network (2011)
  12. Williams, Graham: Data Mining with Rattle and R. The art of excavating data for knowledge discovery. (2011)
  13. Michael Lawrence; Duncan Temple Lang: RGtk2: A Graphical User Interface Toolkit for R (2010) not zbMATH
  14. Wollschläger, Daniel: Foundations of data analysis with R. An application oriented introduction. (2010)
  15. Michael Lawrence; Dianne Cook; Eun-Kyung Lee; Heather Babka; Eve Wurtele: explorase: Multivariate Exploratory Analysis and Visualization for Systems Biology (2008) not zbMATH