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  2. 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]

  3. Informal methods of validation and verification - Wikipedia

    en.wikipedia.org/wiki/Informal_methods_of...

    Inspection is a verification method that is used to compare how correctly the conceptual model matches the executable model. Teams of experts, developers, and testers will thoroughly scan the content (algorithms, programming code, documents, equations) in the original conceptual model and compare with the appropriate counterpart to verify how closely the executable model matches. [1]

  4. Verification and validation - Wikipedia

    en.wikipedia.org/wiki/Verification_and_validation

    Verification is intended to check that a product, service, or system meets a set of design specifications. [6] [7] In the development phase, verification procedures involve performing special tests to model or simulate a portion, or the entirety, of a product, service, or system, then performing a review or analysis of the modeling results.

  5. Software verification and validation - Wikipedia

    en.wikipedia.org/wiki/Software_verification_and...

    Validation during the software development process can be seen as a form of User Requirements Specification validation; and, that at the end of the development process is equivalent to Internal and/or External Software validation. Verification, from CMMI's point of view, is evidently of the artifact kind.

  6. Cross-validation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Cross-validation_(statistics)

    One by one, a set is selected as inner test (validation) set and the l - 1 other sets are combined into the corresponding inner training set. This is repeated for each of the l sets. The inner training sets are used to fit model parameters, while the outer test set is used as a validation set to provide an unbiased evaluation of the model fit.

  7. Verification and validation of computer simulation models

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

    Naylor and Finger [1967] formulated a three-step approach to model validation that has been widely followed: [1] Step 1. Build a model that has high face validity. Step 2. Validate model assumptions. Step 3. Compare the model input-output transformations to corresponding input-output transformations for the real system. [5]

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