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Accuracy ranked from 73%to82%2% in main variables.
After training regression models for the predictable gene set using 2/3 of the TCGA data, the average accuracy (ranked correlation of true and predicted values) in the 1/3 testing partition and four independent populations is above 0.65 and approaches 0.8 for conservative parameter sets.
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The study showed that under dark and dim environments, the TMOs' accuracy ranking obtained was different than that for the bright lighting level environments.
In the external validation, there were considerable fluctuations in the combined accuracy ranking.
Average predictive accuracies ranking with different classifiers of: a C4.5, b KNN, c NB, d SVM, and e all classifiers, obtain from the non-parametric Friedman test and the critical difference (CD) of the Nemenyi post hoc test.
The performance is evaluated by root mean squared error representing the accuracy, rank error representing the suitability of metamodels when coupled with evolutionary optimization algorithms, training time representing the efficiency and variation of root mean squared error representing the robustness.
When using that algorithm with the above protocols, including the three image gallery training process, the V1-like algorithm achieves 97.5% accuracy (rank one recognition) on FERET240 and 41.3% on LFW610.
It is interesting though that for both ANN and SAM the 30-band cases have more unclassified pixels than either the 194- or the 13-band cases and that the exclusion of the unclassified test pixels from the accuracy calculation results in a reversal of the accuracy ranking between the 13- and the 30-band maps.
In the internal validation, Mean top 50% achieved the highest accuracy ranks across all feature set sizes, whereas PCA achieved the lowest accuracy ranks.
Fourth, ASSESS achieved the second highest accuracy rank in both validations.
Third, Mean CORGs achieved a medium accuracy rank in both validations.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com