2014 · 132 citations · 3 references
ComputingComputer ScienceVisualizationBig Data AnalyticsData MiningMachine LearningData PreprocessingText MiningAssociation Rule MiningData Stream MiningMachine Learning SoftwareStream MiningStreaming Data MiningTool Design
This expert paper describes the characteristics of six most used free software tools for general data mining that are available today: RapidMiner, R, Weka, KNIME, Orange, and scikit-learn. The goal is to provide the interested researcher with all the important pros and cons regarding the use of a particular tool. A comparison of the implemented algorithms covering all areas of data mining (classification, regression, clustering, associative rules, feature selection, evaluation criteria, visualization, etc.) is provided. In addition, the tools' support for the more advanced and specialized research topics (big data, data streams, text mining, etc.) is outlined, where applicable. The tools are also compared with respect to the community support, based on the available sources. This multidimensional overview in the form of expert paper on data mining tools emphasizes the quality of RapidMiner, R, Weka, and KNIME platforms, but also acknowledges the significant advancements made in the other tools.
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Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.7K citations · Full text
Mark Hall, Eibe Frank, Geoffrey Holmes et al. · ACM SIGKDD Explorations Newsletter · 2009 · 17.8K citations
Orange: data mining toolbox in python
Janez Demšar, Tomaž Curk, Aleš Erjavec et al. · Journal of Machine Learning Research · 2013 · 1.6K citations