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  2. 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.

  3. Information visualization reference model - Wikipedia

    en.wikipedia.org/wiki/Information_visualization...

    The Information visualization reference model is an example of a reference model for information visualization, developed by Ed Chi in 1999, [1] under the name of the data state model. Chi showed that the framework successfully modeled a wide array of visualization applications and later showed that the model was functionally equivalent to the ...

  4. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  5. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    The data modeling process. The figure illustrates the way data models are developed and used today . A conceptual data model is developed based on the data requirements for the application that is being developed, perhaps in the context of an activity model.

  6. Enterprise data modelling - Wikipedia

    en.wikipedia.org/wiki/Enterprise_data_modelling

    Enterprise data modelling or enterprise data modeling (EDM) is the practice of creating a graphical model of the data used by an enterprise or company. Typical outputs of this activity include an enterprise data model consisting of entity–relationship diagrams (ERDs), XML schemas (XSD), and an enterprise wide data dictionary .

  7. Learning curve (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Learning_curve_(machine...

    In machine learning (ML), a learning curve (or training curve) is a graphical representation that shows how a model's performance on a training set (and usually a validation set) changes with the number of training iterations (epochs) or the amount of training data. [1]

  8. Database model - Wikipedia

    en.wikipedia.org/wiki/Database_model

    Various physical data models can implement any given logical model. Most database software will offer the user some level of control in tuning the physical implementation, since the choices that are made have a significant effect on performance. A model is not just a way of structuring data: it also defines a set of operations that can be ...

  9. Dataflow programming - Wikipedia

    en.wikipedia.org/wiki/Dataflow_programming

    A pioneer dataflow language was BLOck DIagram , published in 1961 by John Larry Kelly, Jr., Carol Lochbaum and Victor A. Vyssotsky for specifying sampled data systems. [9] A BLODI specification of functional units (amplifiers, adders, delay lines, etc.) and their interconnections was compiled into a single loop that updated the entire system ...