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

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

    The first version of the methodology was presented at the 4th CRISP-DM SIG Workshop in Brussels in March 1999, [5] and published as a step-by-step data mining guide later that year. [6] Between 2006 and 2008, a CRISP-DM 2.0 SIG was formed, and there were discussions about updating the CRISP-DM process model. [7]

  3. SEMMA - Wikipedia

    en.wikipedia.org/wiki/SEMMA

    SEMMA is an acronym that stands for Sample, Explore, Modify, Model, and Assess. It is a list of sequential steps developed by SAS Institute, one of the largest producers of statistics and business intelligence software. It guides the implementation of data mining applications. [1]

  4. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    Neither the data collection, data preparation, nor result interpretation and reporting is part of the data mining step, although they do belong to the overall KDD process as additional steps. The difference between data analysis and data mining is that data analysis is used to test models and hypotheses on the dataset, e.g., analyzing the ...

  5. Data preprocessing - Wikipedia

    en.wikipedia.org/wiki/Data_Preprocessing

    Semantic data mining is a subset of data mining that specifically seeks to incorporate domain knowledge, such as formal semantics, into the data mining process.Domain knowledge is the knowledge of the environment the data was processed in. Domain knowledge can have a positive influence on many aspects of data mining, such as filtering out redundant or inconsistent data during the preprocessing ...

  6. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    [6] 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.

  7. 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]

  8. College Football Playoff predictions: Projecting who would ...

    www.aol.com/college-football-playoff-predictions...

    The second of the six College Football Playoff rankings will air on ESPN on Tuesday, Nov. 12, at 8:30 p.m. ET. The second rankings will be revealed between college basketball games in the ...

  9. Data model - Wikipedia

    en.wikipedia.org/wiki/Data_model

    Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.