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

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

    A review and critique of data mining process models in 2009 called the CRISP-DM the "de facto standard for developing data mining and knowledge discovery projects." [16] Other reviews of CRISP-DM and data mining process models include Kurgan and Musilek's 2006 review, [8] and Azevedo and Santos' 2008 comparison of CRISP-DM and SEMMA. [9]

  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.

  5. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]

  6. Crisp - Wikipedia

    en.wikipedia.org/wiki/Crisp

    Potato crisp, a thin slice of a potato deep fried or baked until crispy, known in American English as a potato chip; Crisp (snack type) Crisp (dessert), a type of American dessert, usually including fruit; Crisp (chocolate bar), a Nestlé brand of wafer candy sold in the United States; Simit, in Ottoman cuisine, a circular bread

  7. List of text mining methods - Wikipedia

    en.wikipedia.org/wiki/List_of_text_mining_methods

    Different text mining methods are used based on their suitability for a data set. Text mining is the process of extracting data from unstructured text and finding patterns or relations. Below is a list of text mining methodologies. Centroid-based Clustering: Unsupervised learning method. Clusters are determined based on data points. [1]

  8. Rough set - Wikipedia

    en.wikipedia.org/wiki/Rough_set

    Rough set-based data analysis methods have been successfully applied in bioinformatics, economics and finance, medicine, multimedia, web and text mining, signal and image processing, software engineering, robotics, and engineering (e.g. power systems and control engineering). Recently the three regions of rough sets are interpreted as regions ...

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

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

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