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The performance of the proposed system, evaluated in terms of percent classification, indicated an averaged accuracy of 91.36% for off-line test.
The total correct percent (classification success rate) of the classified lithofacies was automatically calculated after computing the count of success and fail points.
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Classification accuracies (percent correct classification; the chance level was 12.5%) were transformed to z-scores using a binomial distribution and the resulting maps were thresholded at P = 0.01 (uncorrected).
Percent correct classification is based on the overall success of the total sample's cumulative classification in this manner.
One hundred percent correct classification was achieved for the two parental types RR and LL, whereas correct classification of hybrids was only between 80 and 90%.
The commonly used performance metric for a classifier is the percent correct classification.
Table 2 shows these, as well as the sensitivity, specificity, positive and negative PVs, and percent correct classification calculated from them.
To evaluate the effectiveness of this approach, we compared our percent cropland classification with the RUCC for metropolitan (metro) and non-metropolitan areas (nonmetro) in our data.
Results from the PLS-DA models show extremely high sensitivities, specificities, and percent correct classification, albeit with relatively high values for RMSEP.
Predictive criterion-related validity of the clinical diagnostic criteria was assessed by calculating the specificity, sensitivity, percent correct classification and positive likelihood (Attia, 2003), using pathological diagnosis as the gold standard.
To test how significantly different the percent correct classification was from chance, the data epochs were randomly shuffled (meaning that they were assigned incorrect labels) 100 times, the training and testing repeated, and a null distribution of mean classification accuracy created (the dotted lines in Fig. 3 indicate the 95th percentile of the null distributions).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com