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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Stucco project The Stucco project collects data not typically integrated into security systems. This data is not pre-processed Project's website with data information Reviewed source with links to data sources [377] Farsightsecurity Website with technical information, reports, and more about security topics. This data is not pre-processed

  3. Massive Online Analysis - Wikipedia

    en.wikipedia.org/wiki/Massive_Online_Analysis

    Massive Online Analysis (MOA) is a free open-source software project specific for data stream mining with concept drift. It is written in Java and developed at the University of Waikato, New Zealand. [2]

  4. Conceptual clustering - Wikipedia

    en.wikipedia.org/wiki/Conceptual_clustering

    Conceptual clustering is a machine learning paradigm for unsupervised classification that has been defined by Ryszard S. Michalski in 1980 (Fisher 1987, Michalski 1980) and developed mainly during the 1980s. It is distinguished from ordinary data clustering by generating a concept description for each generated class.

  5. Tanagra (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Tanagra_(machine_learning)

    Tanagra is a free suite of machine learning software for research and academic purposes developed by Ricco Rakotomalala at the Lumière University Lyon 2, France. [1] [2] Tanagra supports several standard data mining tasks such as: Visualization, Descriptive statistics, Instance selection, feature selection, feature construction, regression, factor analysis, clustering, classification and ...

  6. Decision tree learning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_learning

    Open source examples include: ALGLIB, a C++, C# and Java numerical analysis library with data analysis features (random forest) KNIME, a free and open-source data analytics, reporting and integration platform (decision trees, random forest) Orange, an open-source data visualization, machine learning and data mining toolkit (random forest)

  7. C4.5 algorithm - Wikipedia

    en.wikipedia.org/wiki/C4.5_algorithm

    C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan. [1] C4.5 is an extension of Quinlan's earlier ID3 algorithm.The decision trees generated by C4.5 can be used for classification, and for this reason, C4.5 is often referred to as a statistical classifier.

  8. Oracle Data Mining - Wikipedia

    en.wikipedia.org/wiki/Oracle_Data_Mining

    Oracle Data Mining (ODM) is an option of Oracle Database Enterprise Edition. It contains several data mining and data analysis algorithms for classification, prediction, regression, associations, feature selection, anomaly detection, feature extraction, and specialized analytics.

  9. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    There have been some efforts to define standards for the data mining process, for example, the 1999 European Cross Industry Standard Process for Data Mining (CRISP-DM 1.0) and the 2004 Java Data Mining standard (JDM 1.0). Development on successors to these processes (CRISP-DM 2.0 and JDM 2.0) was active in 2006 but has stalled since.