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  2. Educational data mining - Wikipedia

    en.wikipedia.org/wiki/Educational_data_mining

    Educational data mining (EDM) is a research field concerned with the application of data mining, ... behaviours and motivation to learn. The ...

  3. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    The term data mining appeared around 1990 in the database community, with generally positive connotations. For a short time in 1980s, the phrase "database mining"™, was used, but since it was trademarked by HNC, a San Diego–based company, to pitch their Database Mining Workstation; [11] researchers consequently turned to data mining.

  4. Examples of data mining - Wikipedia

    en.wikipedia.org/wiki/Examples_of_data_mining

    Metabolomics is a very data heavy subject, and often involves sifting through massive amounts of irrelevant data before finding any conclusions. Data mining has allowed this relatively new field of medical research to grow considerably within the last decade, and will likely be the method of which new research is found within the subject. [28]

  5. OLAP cube - Wikipedia

    en.wikipedia.org/wiki/OLAP_cube

    An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [ 2 ] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.

  6. Feature scaling - Wikipedia

    en.wikipedia.org/wiki/Feature_scaling

    Feature standardization makes the values of each feature in the data have zero-mean (when subtracting the mean in the numerator) and unit-variance. This method is widely used for normalization in many machine learning algorithms (e.g., support vector machines , logistic regression , and artificial neural networks ).

  7. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    The initial motivation is to study the shape of data. TDA has combined algebraic topology and other tools from pure mathematics to allow mathematically rigorous study of "shape". The main tool is persistent homology, an adaptation of homology to point cloud data. Persistent homology has been applied to many types of data across many fields.

  8. Data Science and Predictive Analytics - Wikipedia

    en.wikipedia.org/wiki/Data_Science_and...

    The significantly reorganized revised edition of the book (2023) [2] expands and modernizes the presented mathematical principles, computational methods, data science techniques, model-based machine learning and model-free artificial intelligence algorithms. The 14 chapters of the new edition start with an introduction and progressively build ...

  9. Data monetization - Wikipedia

    en.wikipedia.org/wiki/Data_monetization

    Identification of available data sources – this includes data currently available for monetization as well as other external data sources that may enhance the value of what’s currently available. Connect, aggregate, attribute, validate, authenticate, and exchange data - this allows data to be converted directly into actionable or revenue ...