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  2. Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Receiver_operating...

    ROC curve of three predictors of peptide cleaving in the proteasome. A receiver operating characteristic curve, or ROC curve, is a graphical plot that illustrates the performance of a binary classifier model (can be used for multi class classification as well) at varying threshold values.

  3. Receiver Operating Characteristic Curve Explorer and Tester

    en.wikipedia.org/wiki/Receiver_Operating...

    ROC curves plot the sensitivity of a biomarker on the y axis, against the false discovery rate (1- specificity) on the x axis. An image of different ROC curves is shown in Figure 1. ROC curves provide a simple visual method for one to determine the boundary limit (or the separation threshold) of a biomarker or a combination of biomarkers for ...

  4. Sensitivity and specificity - Wikipedia

    en.wikipedia.org/wiki/Sensitivity_and_specificity

    The 'worst-case' sensitivity or specificity must be calculated in order to avoid reliance on experiments with few results. For example, a particular test may easily show 100% sensitivity if tested against the gold standard four times, but a single additional test against the gold standard that gave a poor result would imply a sensitivity of ...

  5. Total operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Total_operating_characteristic

    The receiver operating characteristic (ROC) also characterizes diagnostic ability, although ROC reveals less information than the TOC. For each threshold, ROC reveals two ratios, hits/(hits + misses) and false alarms/(false alarms + correct rejections), while TOC shows the total information in the contingency table for each threshold. [2]

  6. Partial Area Under the ROC Curve - Wikipedia

    en.wikipedia.org/wiki/Partial_Area_Under_the_ROC...

    The ROC curve is created by plotting the true positive rate (TPR) against the false positive rate (FPR) at various threshold settings. An example of ROC curve and the area under the curve (AUC). The area under the ROC curve (AUC) [1] [2] is often used to summarize in a single number the diagnostic ability of the classifier. The AUC is simply ...

  7. Detection error tradeoff - Wikipedia

    en.wikipedia.org/wiki/Detection_error_tradeoff

    The x- and y-axes are scaled non-linearly by their standard normal deviates (or just by logarithmic transformation), yielding tradeoff curves that are more linear than ROC curves, and use most of the image area to highlight the differences of importance in the critical operating region.

  8. Laboratory quality control - Wikipedia

    en.wikipedia.org/wiki/Laboratory_quality_control

    A control chart is a more specific kind of run chart. The control chart is one of the seven basic tools of quality control, which also include the histogram, pareto chart, check sheet, cause and effect diagram, flowchart and scatter diagram. Control charts prevent unnecessary process adjustments, provide information about process capability ...

  9. Tornado diagram - Wikipedia

    en.wikipedia.org/wiki/Tornado_diagram

    Completed Tornado Diagram. Tornado diagrams, also called tornado plots, tornado charts or butterfly charts, are a special type of Bar chart, where the data categories are listed vertically instead of the standard horizontal presentation, and the categories are ordered so that the largest bar appears at the top of the chart, the second largest appears second from the top, and so on.