The question is - is the error being amplified or is the accuracy being amplified?
in high variance systems, it appears, that the model ends up emulating different sections of the data set. From the point of veiw of the statistical measures of accuracy, models with very different ____ qualities, may appear equivalent.
Since this situation would always be reflected in higher error in atleast one of the three error values, we at least know when the model is definitely incomplete. an objective measure of completeness is not easily found because we do not have information other than the training data (which is called - lack of meta data) to compare it with. an issue resulting from dealing with a largly unknown system.
Regarding Sensitivity Analysis
if similarities are found between complete models and incomplete models -
can it be concluded -
that the similarities are strongly persistent in the entire set.
(data and random nos. should not give the same kinds of results - ... does this need any more work to be done.
eventually, the results of sensitivity analysis is dependent on
- the raw data,
- the neural network model
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