Accuracy is how close a given set of measurements (observations or readings) are to their true value. Precision is how close the measurements are to each other.
Data quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality.
Data integrity is the maintenance of, and the assurance of, data accuracy and consistency over its entire life-cycle.
Accuracy is a weighted arithmetic mean of Precision and Inverse Precision ... Accuracy can be a misleading metric for imbalanced data sets. Consider a ...
Quality of Data (QoD) is a designation coined by L. Veiga, that specifies and describes the required Quality of Service of a distributed storage system
The accuracy paradox is the paradoxical finding that accuracy is not a good metric for predictive models when classifying in predictive analytics.
Sensitivity is a measure of how well a test can identify true positives and specificity is a measure of how well a test can identify true negatives.
Data verification is a process in which different types of data are checked for accuracy and inconsistencies after data migration is done.
False precision occurs when numerical data are presented in a manner that implies better precision than is justified; since precision is a limit to accuracy ...
The term data reliability may refer to: Reliability (statistics), the overall consistency of a measure; Data integrity, the maintenance of, ...