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The general formula for non-negative real ... Mean average precision (MAP) for a set of queries is the mean of the average precision scores for each query.
It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [ 3 ]
Mean average precision (MAP); DCG and NDCG; Precision@n, NDCG@n, where "@n" denotes that the metrics are evaluated only on top n documents; Mean reciprocal rank; Kendall's tau; Spearman's rho. DCG and its normalized variant NDCG are usually preferred in academic research when multiple levels of relevance are used. [11]
In medicine, the mean arterial pressure (MAP) is an average calculated blood pressure in an individual during a single cardiac cycle. [1] Although methods of estimating MAP vary, a common calculation is to take one-third of the pulse pressure (the difference between the systolic and diastolic pressures), and add that amount to the diastolic pressure.
In a classification task, the precision for a class is the number of true positives (i.e. the number of items correctly labelled as belonging to the positive class) divided by the total number of elements labelled as belonging to the positive class (i.e. the sum of true positives and false positives, which are items incorrectly labelled as belonging to the class).
The earliest reference to a similar formula appears to be Armstrong (1985, p. 348), where it is called "adjusted MAPE" and is defined without the absolute values in the denominator. It was later discussed, modified, and re-proposed by Flores (1986).
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This page was last edited on 25 April 2018, at 16:47 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...