Precision

closeness of agreement between indications or measured quantity values obtained by replicate measurements on the same or similar objects under specified conditions

A metric for classification models. Precision identifies the frequency with which a model was correct when predicting the positive class. That is: Precision = True Positive /(True Positive + False Positive)

A metric for classification models. Precision identifies the frequency with which a model was correct when classifying the positive class.

Closeness of agreement between independent test results obtained under prescribed conditions. It is generally dependent on analyte concentration, and this dependence should be determined and documented. The measure of precision is usually expressed in terms of imprecision and computed as a standard deviation of the test results. Higher imprecision is reflected by a larger standard deviation. Independent test results means results obtained in a manner not influenced by any previous results on the same or similar material. Precision covers repeatability and reproducibility [19]. Alternatively, precision is a measure for the reproducibility of measurements within a set, that is, of the scatter or dispersion of a set about its central value. Precision depends only on the distribution of random errors and does not relate to the true value or specified value.