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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]
Color accuracy is an important but ambiguous image quality factor. Many viewers prefer enhanced color saturation; the most accurate color isn't necessarily the most pleasing. Nevertheless, it is important to measure a camera's color response: its color shifts, saturation, and the effectiveness of its white balance algorithms.
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).
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.
In information retrieval, the positive predictive value is called precision, and sensitivity is called recall. Unlike the Specificity vs Sensitivity tradeoff, these measures are both independent of the number of true negatives, which is generally unknown and much larger than the actual numbers of relevant and retrieved documents.
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.
It lacks accuracy in differentiating between fat mass and muscle mass, which could falsely diagnose people with high muscle mass as having obesity. It also doesn’t account for variations in body ...
Likewise, with digital cameras, images taken at higher sensitivity settings show more image noise than those taken at lower sensitivities. [ 6 ] However, even if both techniques have inherent noise, it is widely appreciated that for color, digital photography has much less noise/grain than film at equivalent sensitivity, leading to an edge in ...