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To evaluate top-5 accuracy, the classifier must provide relative likelihoods for each class. When these are sorted, a classification is considered correct if the correct classification falls anywhere within the top 5 predictions made by the network. Top-5 accuracy was popularized by the ImageNet challenge. It is usually higher than top-1 ...
Provided the data are strictly positive, a better measure of relative accuracy can be obtained based on the log of the accuracy ratio: log(F t / A t) This measure is easier to analyze statistically and has valuable symmetry and unbiasedness properties
This little-known but serious issue can be overcome by using an accuracy measure based on the logarithm of the accuracy ratio (the ratio of the predicted to actual value), given by (). This approach leads to superior statistical properties and also leads to predictions which can be interpreted in terms of the geometric mean.
Best rational approximants for π (green circle), e (blue diamond), ϕ (pink oblong), (√3)/2 (grey hexagon), 1/√2 (red octagon) and 1/√3 (orange triangle) calculated from their continued fraction expansions, plotted as slopes y/x with errors from their true values (black dashes)
Alternative formulations may include relative frequencies as weight factors. ... This is known as a scale-dependent accuracy measure and ... it is simply the average ...
The absolute change in this situation is 1 percentage point (4% − 3%), but the relative change in the interest rate is: % % % = … = %. In general, the term "percentage point(s)" indicates an absolute change or difference of percentages, while the percent sign or the word "percentage" refers to the relative change or difference.
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RMSD is a measure of accuracy, to compare forecasting errors of different models for a particular dataset and not between datasets, as it is scale-dependent. [ 1 ] RMSD is always non-negative, and a value of 0 (almost never achieved in practice) would indicate a perfect fit to the data.