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

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

    Provides many tasks from classification to QA, and various languages from English, Portuguese to Arabic. Appen : Off The Shelf and Open Source Datasets hosted and maintained by the company. These biological, image, physical, question answering, signal, sound, text, and video resources number over 250 and can be applied to over 25 different use ...

  3. Power Pivot - Wikipedia

    en.wikipedia.org/wiki/Power_Pivot

    Practically, this means that Power Pivot is acting as an Analysis Services Server instance on the local workstation. As a result, larger data models may not be compatible with the 32-bit version of Excel. Data Analysis Expressions (DAX) is the primary expression language, although the model can also be queried via Multi Dimensional Expressions ...

  4. ModelSheet - Wikipedia

    en.wikipedia.org/wiki/ModelSheet

    ModelSheet was founded by two MIT graduates, Richard Petti and Howard Cannon, who earlier worked together at Symbolics and later in the division spun out as Macsyma. [1] [non-primary source needed] After the Macsyma episode in the 1980s and the 1990s, the pair took separate career paths, with Petti at The MathWorks, and Cannon at Groton NeoChem and SciQuest, and then merged their companies to ...

  5. Data classification (data management) - Wikipedia

    en.wikipedia.org/wiki/Data_classification_(data...

    Data classification is the process of organizing data into categories based on attributes like file type, content, or metadata. The data is then assigned class labels that describe a set of attributes for the corresponding data sets. The goal is to provide meaningful class attributes to former less structured information.

  6. Probabilistic classification - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_classification

    Formally, an "ordinary" classifier is some rule, or function, that assigns to a sample x a class label ลท: ^ = The samples come from some set X (e.g., the set of all documents, or the set of all images), while the class labels form a finite set Y defined prior to training.

  7. Data classification (business intelligence) - Wikipedia

    en.wikipedia.org/wiki/Data_classification...

    The first step in doing a data classification is to cluster the data set used for category training, to create the wanted number of categories. An algorithm, called the classifier, is then used on the categories, creating a descriptive model for each. These models can then be used to categorize new items in the created classification system. [2]

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  9. Associative classifier - Wikipedia

    en.wikipedia.org/wiki/Associative_classifier

    The model generated by an AC and used to label new records consists of association rules, where the consequent corresponds to the class label.As such, they can also be seen as a list of "if-then" clauses: if the record matches some criteria (expressed in the left side of the rule, also called antecedent), it is then labeled accordingly to the class on the right side of the rule (or consequent).