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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]
MCL: Model Checking Language; Alternation-Free Modal μ-calculus extended with user-friendly regular expressions and value-passing constructs; subsumes CTL and LTL. mCRL2 mu-calculus: Kozen's propositional modal μ-calculus (excluding atomic propositions), extended with: data-depended processes, quantification over data types, multi-actions ...
Bean Validation defines a metadata model and API for JavaBean validation. The metadata source is annotations, with the ability to override and extend the meta-data through the use of XML validation descriptors. Originally defined as part of Java EE, version 2 aims to work in Java SE apps as well.
Residual plots plot the difference between the actual data and the model's predictions: correlations in the residual plots may indicate a flaw in the model. Cross validation is a method of model validation that iteratively refits the model, each time leaving out just a small sample and comparing whether the samples left out are predicted by the ...
If an independent sample of validation data is taken from the same population as the training data, it will generally turn out that the model does not fit the validation data as well as it fits the training data. The size of this difference is likely to be large especially when the size of the training data set is small, or when the number of ...
The fitted model is evaluated using “new” examples from the held-out data sets (validation and test data sets) to estimate the model’s accuracy in classifying new data. [5] To reduce the risk of issues such as over-fitting, the examples in the validation and test data sets should not be used to train the model. [5]
Model checking is also studied in the field of computational complexity theory. Specifically, a first-order logical formula is fixed without free variables and the following decision problem is considered: Given a finite interpretation, for instance, one described as a relational database, decide whether the interpretation is a model of the ...
M&S Validation is the process of determining the degree to which a model, simulation, or federation of models and simulations, and their associated data are accurate representations of the real world from the perspective of the intended use(s). [3]