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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 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 measure precision at k, for example, is a measure of precision looking only at the top ten (k=10) search results. More sophisticated metrics, such as discounted cumulative gain , take into account each individual ranking, and are more commonly used where this is important.
The measure precision at k, for example, is a measure of precision looking only at the top ten (k=10) search results. More sophisticated metrics, such as discounted cumulative gain , take into account each individual ranking, and are more commonly used where this is important.
Traditional evaluation metrics, designed for Boolean retrieval [clarification needed] or top-k retrieval, include precision and recall. All measures assume a ground truth notion of relevance: every document is known to be either relevant or non-relevant to a particular query.
Precision and recall. In statistical analysis of binary classification and information retrieval systems, the F-score or F-measure is a measure of predictive performance. It is calculated from the precision and recall of the test, where the precision is the number of true positive results divided by the number of all samples predicted to be positive, including those not identified correctly ...
Eidetic memory (/ aɪ ˈ d ɛ t ɪ k / eye-DET-ik), also known as photographic memory and total recall, is the ability to recall an image from memory with high precision—at least for a brief period of time—after seeing it only once [1] and without using a mnemonic device.
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 ...