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  2. Data validation - Wikipedia

    en.wikipedia.org/wiki/Data_validation

    Overview. Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1] Their implementation can use declarative data integrity rules, or ...

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

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

    In particular, three data sets are commonly used in different stages of the creation of the model: training, validation, and test sets. The model is initially fit on a training data set, [3] which is a set of examples used to fit the parameters (e.g. weights of connections between neurons in artificial neural networks) of the model. [4]

  4. Verification and validation - Wikipedia

    en.wikipedia.org/wiki/Verification_and_validation

    Verification and validation. Verification and validation (also abbreviated as V&V) are independent procedures that are used together for checking that a product, service, or system meets requirements and specifications and that it fulfills its intended purpose. [1] These are critical components of a quality management system such as ISO 9000.

  5. Software verification and validation - Wikipedia

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

    Software verification and validation. In software project management, software testing, and software engineering, verification and validation is the process of checking that a software engineer system meets specifications and requirements so that it fulfills its intended purpose. It may also be referred to as software quality control.

  6. Verification and validation of computer simulation models

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

    Verification and validation of computer simulation models. Verification and validation of computer simulation models is conducted during the development of a simulation model with the ultimate goal of producing an accurate and credible model. [1][2] "Simulation models are increasingly being used to solve problems and to aid in decision-making.

  7. Statistical model validation - Wikipedia

    en.wikipedia.org/wiki/Statistical_model_validation

    In statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences from models that appear to fit their data may be flukes, resulting in a misunderstanding by researchers of the actual relevance of their model. To combat this, model validation is ...

  8. Luhn algorithm - Wikipedia

    en.wikipedia.org/wiki/Luhn_algorithm

    Luhn algorithm. The Luhn algorithm or Luhn formula, also known as the " modulus 10" or "mod 10" algorithm, named after its creator, IBM scientist Hans Peter Luhn, is a simple check digit formula used to validate a variety of identification numbers. It is described in US patent 2950048A, granted on 23 August 1960. [1]

  9. Data validation and reconciliation - Wikipedia

    en.wikipedia.org/wiki/Data_validation_and...

    Industrial process data validation and reconciliation, or more briefly, process data reconciliation (PDR), is a technology that uses process information and mathematical methods in order to automatically ensure data validation and reconciliation by correcting measurements in industrial processes. The use of PDR allows for extracting accurate ...