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  2. Spaghetti plot - Wikipedia

    en.wikipedia.org/wiki/Spaghetti_plot

    Within meteorology, spaghetti diagrams are normally drawn from ensemble forecasts. A meteorological variable e.g. pressure, temperature, or precipitation amount is drawn on a chart for a number of slightly different model runs from an ensemble. The model can then be stepped forward in time and the results compared and be used to gauge the ...

  3. Structured analysis and design technique - Wikipedia

    en.wikipedia.org/wiki/Structured_Analysis_and...

    SADT uses two types of diagrams: activity models and data models. It uses arrows to build these diagrams. The SADT's representation is the following: A main box where the name of the process or the action is specified; On the left-hand side of this box, incoming arrows: inputs of the action.

  4. MagicDraw - Wikipedia

    en.wikipedia.org/wiki/MagicDraw

    Fully customizable templates can be created in the style and format preferred by the user. Reports can be exported into variety of file formats (OpenDocument (*.odt), RTF (*.rtf), Microsoft Word (*.docx), Microsoft Excel (*.xlsx), Microsoft PowerPoint (*.pptx), XML, HTML, XHTML). Reports can be personalized with characters, paragraphs, and ...

  5. ADDIE model - Wikipedia

    en.wikipedia.org/wiki/ADDIE_Model

    ADDIE is an instructional systems design (ISD) framework that many instructional designers and training developers use to develop courses. [1] The name is an acronym for the five phases it defines for building training and performance support tools: Analysis; Design; Development; Implementation; Evaluation

  6. 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]

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