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Olexa Riznyk (talk | contribs) →Methods for validating: Adding Turing test wikilink |
Olexa Riznyk (talk | contribs) →Overview: Adding Statistical model validation#Residual diagnostics wikilink |
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==Overview==
Model validation can be based on two types of data: data that was used in the construction of the model and data that was not used in the construction. Validation based on the first type usually involves analyzing the [[goodness of fit]] of the model or analyzing whether the [[Errors and residuals|residuals]] seem to be random (i.e. [[#Residual diagnostics|residual diagnostics]]). Validation based on the second type usually involves analyzing whether the model's [[Prediction interval|predictive performance]] deteriorates non-negligibly when applied to pertinent new data.
[[Image:Overfitted Data.png|thumb|300px|Figure 1. Data (black dots), which was generated via the straight line and some added noise, is perfectly fitted by a curvy [[polynomial]].]]
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