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  2. Model output statistics - Wikipedia

    en.wikipedia.org/wiki/Model_output_statistics

    In weather forecasting, model output statistics (MOS) is a multiple linear regression technique in which predictands, often near-surface quantities (such as two-meter-above-ground-level air temperature, horizontal visibility, and wind direction, speed and gusts), are related statistically to one or more predictors.

  3. Simulation decomposition - Wikipedia

    en.wikipedia.org/wiki/Simulation_decomposition

    Assign scenarios to each output value. The simulation data is used to define the scenario index for each simulation run. For example, if an X2 value falls into the low state and X3 is equal to 2, the corresponding scenario, defined in Step 3, is (ii). Color-code the output distribution. When all output values are assigned scenario indices, they ...

  4. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Following document retrieval, the LLM generates an output that incorporates information from both the query and the retrieved documents. [50] This method is particularly beneficial for handling proprietary or dynamic information that was not included in the initial training or fine-tuning phases of the model.

  5. Verification and validation of computer simulation models

    en.wikipedia.org/wiki/Verification_and...

    Comparing curves with fixed sample size tradeoffs between model builder's risk and model user's risk can be seen easily in the risk curves. [7] If model builder's risk, model user's risk, and the upper and lower limits for the range of accuracy are all specified then the sample size needed can be calculated. [7]

  6. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    It makes some of the old CRISP-DM documents available for download and it has incorporated it into its SPSS Modeler product. [6] Based on current research, CRISP-DM is the most widely used form of data-mining model because of its various advantages which solved the existing problems in the data mining industries.

  7. Platt scaling - Wikipedia

    en.wikipedia.org/wiki/Platt_scaling

    In machine learning, Platt scaling or Platt calibration is a way of transforming the outputs of a classification model into a probability distribution over classes.The method was invented by John Platt in the context of support vector machines, [1] replacing an earlier method by Vapnik, but can be applied to other classification models. [2]

  8. HIPO model - Wikipedia

    en.wikipedia.org/wiki/HIPO_model

    HIPO model (hierarchical input process output model) is a systems analysis design aid and documentation technique from the 1970s, [1] used for representing the modules of a system as a hierarchy and for documenting each module.

  9. IPO model - Wikipedia

    en.wikipedia.org/wiki/IPO_Model

    The input–process–output model. The input–process–output (IPO) model, or input-process-output pattern, is a widely used approach in systems analysis and software engineering for describing the structure of an information processing program or other process. Many introductory programming and systems analysis texts introduce this as the ...