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  2. 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 ...

  3. 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 ...

  4. Checksum - Wikipedia

    en.wikipedia.org/wiki/Checksum

    Checksum. A checksum is a small-sized block of data derived from another block of digital data for the purpose of detecting errors that may have been introduced during its transmission or storage. By themselves, checksums are often used to verify data integrity but are not relied upon to verify data authenticity. [1]

  5. Generalized additive model - Wikipedia

    en.wikipedia.org/wiki/Generalized_additive_model

    Generalized additive model. In statistics, a generalized additive model (GAM) is a generalized linear model in which the linear response variable depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions. GAMs were originally developed by Trevor Hastie and Robert ...

  6. 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 ...

  7. Cross-validation (statistics) - Wikipedia

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

    Cross-validation includes resampling and sample splitting methods that use different portions of the data to test and train a model on different iterations. It is often used in settings where the goal is prediction, and one wants to estimate how accurately a predictive model will perform in practice.

  8. 'Heartbreaking': Mass. police recruit dies after getting ...

    www.aol.com/news/heartbreaking-mass-police...

    NEW BRAINTREE, Mass. — A Massachusetts family is demanding a full investigation after a Massachusetts state police recruit died after being injured during a training exercise late last week at ...

  9. Data verification - Wikipedia

    en.wikipedia.org/wiki/Data_verification

    Data verification helps to determine whether data was accurately translated when data is transferred from one source to another, is complete, and supports processes in the new system. During verification, there may be a need for a parallel run of both systems to identify areas of disparity and forestall erroneous data loss.