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Accuracy is also used as a statistical measure of how well a binary classification test correctly identifies or excludes a condition. That is, the accuracy is the proportion of correct predictions (both true positives and true negatives) among the total number of cases examined. [10] As such, it compares estimates of pre- and post-test probability.
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 usefulness, accuracy, and correctness of data for its application" [10] Arguably, in all these cases, "data quality" is a comparison of the actual state of a particular set of data to a desired state, with the desired state being typically referred to as "fit for use," "to specification," "meeting consumer expectations," "free of defect ...
The formal definition of calibration by the International Bureau of Weights and Measures (BIPM) is the following: "Operation that, under specified conditions, in a first step, establishes a relation between the quantity values with measurement uncertainties provided by measurement standards and corresponding indications with associated measurement uncertainties (of the calibrated instrument or ...
Quantification of measurement uncertainty, including the accuracy, precision including repeatability and reproducibility, the stability and linearity of these quantities over time and across the intended range of use of the measurement process. Development of improvement plans, when needed.
Measuring the effectiveness of IR systems has been the main focus of IR research, based on test collections combined with evaluation measures. [5] A number of academic conferences have been established that focus specifically on evaluation measures including the Text Retrieval Conference (TREC), Conference and Labs of the Evaluation Forum (CLEF ...
Information retrieval (IR) in computing and information science is the task of identifying and retrieving information system resources that are relevant to an information need.
False precision (also called overprecision, fake precision, misplaced precision, and spurious precision) occurs when numerical data are presented in a manner that implies better precision than is justified; since precision is a limit to accuracy (in the ISO definition of accuracy), this often leads to overconfidence in the accuracy, named precision bias.