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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 ...
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]
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.
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.
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 .
A process-data diagram (PDD), also known as process-deliverable diagram is a diagram that describes processes and data that act as output of these processes. On the left side the meta-process model can be viewed and on the right side the meta-data model can be viewed. [1] A process-data diagram can be seen as combination of a business process ...