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UpSet plots became popular as they became available as an R-library based on ggplot2, [3] and were subsequently re-implemented in various programming languages, such as Python, and others. [4] As of January 2024, UpSetR has been downloaded from CRAN more than 1.5 million times, although it was last updated 5 years ago. [ 5 ]
Each observation plots against its own control limits as determined by the sample size-specific values, n i, of A 3, B 3, and B 4 Use control limits based on an average sample size [ 7 ] Control limits are fixed at the modal (or most common) sample size-specific value of A 3 , B 3 , and B 4
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For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.
For example, if there were 95 cancer samples and only 5 non-cancer samples in the data, a particular classifier might classify all the observations as having cancer. The overall accuracy would be 95%, but in more detail the classifier would have a 100% recognition rate ( sensitivity ) for the cancer class but a 0% recognition rate for the non ...
In contrast to the mean absolute percentage error, SMAPE has both a lower and an upper bound. Indeed, the formula above provides a result between 0% and 200%. Indeed, the formula above provides a result between 0% and 200%.
For example, log scales may give a height of 1 for a value of 10 in the data and a height of 6 for a value of 1,000,000 (10 6) in the data. Log scales and variants are commonly used, for instance, for the volcanic explosivity index, the Richter scale for earthquakes, the magnitude of stars, and the pH of acidic and alkaline solutions.