Data mining (also known as knowledge discovery) is the process of gathering large amounts of valid information, analyzing that information and condensing it into meaningful data.
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Data mining (also known as knowledge discovery) is the process of gathering large amounts of valid information, analyzing that information and condensing it into meaningful data.
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R is a programming language and environment for statistical computing, data analysis and graphics with a vast package ecosystem.
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MOA is a data stream mining framework with online classification, clustering, concept drift detection and tools for evaluating algorithms.
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Orange is a visual data mining application with data exploration, classification, clustering, model evaluation and extensible workflows.
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ELKI is a research-focused data mining toolkit offering clustering, outlier detection, spatial indexing and algorithm evaluation.
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DataMelt is a scientific computation environment with interactive plotting, statistical analysis, fitting and mathematical scripting tools.
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Weka is a data mining workbench with classification, clustering, regression, preprocessing, experiments and extensible workflows.
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Rattle is a graphical data science tool with data preparation, exploration, modelling, evaluation and reproducible R script export.
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ROOT is a scientific data analysis framework with columnar storage, RDataFrame workflows, statistical modelling and machine learning tools.
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KNIME provides visual workflows for data preparation, analysis, machine learning, interactive charts and reusable analytics components.
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RapidMiner is a historical visual data mining platform featuring operator workflows, data preparation, modelling and predictive analytics.
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SAS Enterprise Miner aims to streamline the data mining process. We recommend the best free and open source alternatives.
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Data mining is no longer a mythical thing that only a handful of data scientists understand. Everyone leverages data to do their work.
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