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  2. Receiver operating characteristic - Wikipedia

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

    In medicine, ROC analysis has been extensively used in the evaluation of diagnostic tests. [57] [58] ROC curves are also used extensively in epidemiology and medical research and are frequently mentioned in conjunction with evidence-based medicine. In radiology, ROC analysis is a common technique to evaluate new radiology techniques. [59]

  3. Receiver Operating Characteristic Curve Explorer and Tester

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

    In the multivariate module one can choose between three different techniques – SVM (support vector machine), PLS-DA (partial least squares discriminant analysis) and Random Forests for classifying and selecting metabolites or clinical variables for an optimal ROC performance. The resulting analysis produces the top-performing multi-variable ...

  4. 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]

  5. Youden's J statistic - Wikipedia

    en.wikipedia.org/wiki/Youden's_J_statistic

    Youden's index is often used in conjunction with receiver operating characteristic (ROC) analysis. [3] The index is defined for all points of an ROC curve, and the maximum value of the index may be used as a criterion for selecting the optimum cut-off point when a diagnostic test gives a numeric rather than a dichotomous result.

  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. Talk:Receiver operating characteristic - Wikipedia

    en.wikipedia.org/wiki/Talk:Receiver_operating...

    ROC analysis since then has been used in medicine, radiology, biometrics, forecasting of natural hazards, meteorology, model performance assessment, and other areas for many decades and is increasingly used in machine learning and data mining research.

  8. Research proposal - Wikipedia

    en.wikipedia.org/wiki/Research_proposal

    A research proposal is a document proposing a research project, generally in the sciences or academia, and generally constitutes a request for sponsorship of that research. [1] Proposals are evaluated on the cost and potential impact of the proposed research, and on the soundness of the proposed plan for carrying it out. [2] Research proposals ...

  9. Cumulative accuracy profile - Wikipedia

    en.wikipedia.org/wiki/Cumulative_accuracy_profile

    A cumulative accuracy profile (CAP) is a concept utilized in data science to visualize discrimination power.The CAP of a model represents the cumulative number of positive outcomes along the y-axis versus the corresponding cumulative number of a classifying parameter along the x-axis.