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The AUC is a threshold independent measure of model performance, where an AUC value of 1 indicates optimal performance, and AUC = 0.5 indicates a model performing no better than a randomly generated one.
The AUC statistic is a threshold-independent measure of model performance; theoretically, an AUC score of 1.0 indicates optimal performance, while AUC = 0.5 indicates a model that predicted occurrences no better than at random [40].
AUC value of 1 indicates optimal performance, whilst AUC = 0.5 indicates performance equal to random.
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where * indicates optimal values.
Our experimental results indicate that optimal performance, achieved with unequal feature proportions, could be better than the performance obtained with the commonly used 50 50 feature proportion.
The SeDI and SpDI peak on both sides of the first peak, and indicate the optimal performance when either sensitivity or specificity is the main focus for the test.
Scores 3D scatter plots from PLS-DA results indicated an optimal performance of the model to differentiate big groups of fruits: lemons, grapefruits, oranges and mandarins and, in addition, some varieties were clearly differentiated within their respective groups such as both grapefruit cultivars, 'Pixie' mandarin and 'Sucrenya' blonde orange.
A number of assessments have indicated sub-optimal performance of the health system.
The simulation results follow the lines of the theoretical results, indicating the throughput optimal performance of the BPeMRF scheme, similarly to BP, while by leveraging Gibbs sampling, BPeMRF allows for less complex computations than BP.
Results indicate that the optimal performance is influenced by the non-minimum phase zeros, unstable poles, the scaling parameter matrix, and the characteristics of the communication noise and fading.
If SUs cannot find new channels, even though there are some free channel(s), they are forced to terminate their own connections and hence reducing S U SP. The results shown in Fig. 10 indicate that SU optimal performance is when λ FAR is close to zero.
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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