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  2. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    It makes some of the old CRISP-DM documents available for download and it has incorporated it into its SPSS Modeler product. [6] Based on current research, CRISP-DM is the most widely used form of data-mining model because of its various advantages which solved the existing problems in the data mining industries.

  3. 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.

  4. SEMMA - Wikipedia

    en.wikipedia.org/wiki/SEMMA

    SEMMA mainly focuses on the modeling tasks of data mining projects, leaving the business aspects out (unlike, e.g., CRISP-DM and its Business Understanding phase). Additionally, SEMMA is designed to help the users of the SAS Enterprise Miner software. Therefore, applying it outside Enterprise Miner may be ambiguous. [3]

  5. Talk : Cross-industry standard process for data mining

    en.wikipedia.org/wiki/Talk:Cross-industry...

    5 Inclusion of some CRISP-DM 2.0 material. ... 7 Source link for "CRISP-DM 1.0 Step-by-step data mining guide"? (current one is wrong) Toggle the table of contents.

  6. Oracle Data Mining - Wikipedia

    en.wikipedia.org/wiki/Oracle_Data_Mining

    Oracle Data Mining (ODM) is an option of Oracle Database Enterprise Edition. ... and applying models (e.g. along the lines of the CRISP-DM methodology).

  7. File:CRISP-DM Process Diagram.png - Wikipedia

    en.wikipedia.org/wiki/File:CRISP-DM_Process...

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  8. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    Data mining can be helpful to organizations. Organizational Data Mining (ODM) is defined as leveraging data mining (DM) tools and technologies to enhance organizational decision-making process by transforming data into valuable and actionable knowledge in order to gain a strategic and business competitive advantage.

  9. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.