Overall Accuracy
The proportion of all samples whose predictions are correct in a classification task; it is a basic evaluation metric but is readily affected by the distribution of sample counts across classes.
Timeline (last 90 days)
On the Mixed-WM38 dataset (containing 6,866 wafer maps), the multi-region prompting strategy achieved 92.9% macro-average accuracy and 93.8% overall accuracy.
Apart from the selected optimal rule order, the overall accuracy of the other eight alternative rule orders ranged from 90.1% to 91.9%, all below the 93.8% of the selected order.
Macro-average accuracy first computes the accuracy of each class separately and then takes the arithmetic mean, making it more sensitive to the performance of minority classes; overall accuracy is the proportion of all samples predicted correctly and is easily affected by the class sample size distribution.
All Facts (3)
On the Mixed-WM38 dataset (containing 6,866 wafer maps), the multi-region prompting strategy achieved 92.9% macro-average accuracy and 93.8% overall accuracy.
50%UnverifiedApart from the selected optimal rule order, the overall accuracy of the other eight alternative rule orders ranged from 90.1% to 91.9%, all below the 93.8% of the selected order.
50%UnverifiedMacro-average accuracy first computes the accuracy of each class separately and then takes the arithmetic mean, making it more sensitive to the performance of minority classes; overall accuracy is the proportion of all samples predicted correctly and is easily affected by the class sample size distribution.
50%