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For instance, one can consider the Hamming distances for one or more segments of the MRIPs between the received hard decisions (before the decoding) and the temporary decisions obtained using the test error patterns from the list.
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We then evaluate the root mean square error (RMSE) using the test sets and the regression matrices S ̂ i : RMSE : 1 3 ∑ i = 1 3 1 M TS i × T ∥ A TS i S ̂ i − Y TS i ∥ F, where Y TS i ∈ R M TS i × T, and A TS i ∈ R M TS i × N (TS i denotes the index set of the rows that belongs to the i th test set).
Errors in using the test may be introduced gradually and go unnoticed if experiences and problems are not periodically discussed and evaluated [ 15].
A 95% confidence interval for kappa was computed using the test-based standard error.
Finally, the test data corresponding to the selected channel and feature subset for the trained model under test was used to calculate the test error rate.
Using the testbed, the impacts of the errors were investigated for the safety planning purpose.
However, even though we cannot calculate the test error, it is possible to estimate the expected test error using training samples.
Using the method the testing error achieved was in the order of magnitude of within 10−5 10−3.
The latter estimator is a variant of the well-known 10-fold cross-validation estimator which is calculated by balanced splitting of the data into 10 non-overlapping sample sets used for testing (while each complementing set is used for training) and averaging the test errors.
We tested the models using the regression specification error test (RESET test).
Funnel plots and forest plots were generated and funnel plot asymmetry was tested using the regression test (with standard error as the predictor).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com