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The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results. [3] [4] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method.
A precision-recall curve plots precision as a function of recall; usually precision will decrease as the recall increases. Alternatively, values for one measure can be compared for a fixed level at the other measure (e.g. precision at a recall level of 0.75) or both are combined into a single measure.
Precision takes all retrieved documents into account. It can also be evaluated considering only the topmost results returned by the system using Precision@k. Note that the meaning and usage of "precision" in the field of information retrieval differs from the definition of accuracy and precision within other branches of science and statistics.
In other words, heat always moves from hotter objects to colder objects unless energy is supplied to reverse the direction of heat flow, and not all heat energy can be converted into work in a cyclic process. Semiconductor – Series and parallel circuits – Shear force diagrams – Shear pin – Shear strength – Shear stress – Simple ...
Accuracy and precision, measurement deviation from true value and its scatter; Significant figures, the number of digits that carry real information about a measurement; Precision and recall, in information retrieval: the proportion of relevant documents returned; Precision (computer science), a measure of the detail in which a quantity is ...
Of these, octuple-precision format is rarely used. The single- and double-precision formats are most widely used and supported on nearly all platforms. The use of half-precision format has been increasing especially in the field of machine learning since many machine learning algorithms are inherently error-tolerant.
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Another reason the precision matrix may be useful is that if two dimensions and of a multivariate normal are conditionally independent, then the and elements of the precision matrix are . This means that precision matrices tend to be sparse when many of the dimensions are conditionally independent, which can lead to computational efficiencies ...