Specificity (Data Science): Revision history

From IT위키

Diff selection: Mark the radio buttons of the revisions to compare and hit enter or the button at the bottom.
Legend: (cur) = difference with latest revision, (prev) = difference with preceding revision, m = minor edit.

    4 November 2024

    • curprev 14:1114:11, 4 November 2024‎ 핵톤 talk contribs‎ 2,246 bytes +2,246‎ Created page with "'''Specificity''', also known as the '''True Negative Rate (TNR)''', is a metric used in binary classification to measure the proportion of actual negative cases that are correctly identified by the model. It reflects the model’s ability to avoid false positives and accurately classify negative instances. ==Definition== Specificity is calculated as: :'''<big>Specificity = True Negatives / (True Negatives + False Positives)</big>''' A higher specificity value indicates..." Tag: Visual edit
Retrieved from "https://itwiki.kr/w/Specificity_(Data_Science)"