Assembly: Stat;
The IROCcurve interface is used to work with ROC curve.
IROCcurve
A ROC curve is a graph that enables the user to assess the quality of binary classification. A ROC curve displays relation between the share of objects from the total number of attribute bearers that are correctly identifier as attribute bearers, and the share of objects from the total number of objects that are not attribute bearers and that are by error identifier as attribute bearers on varying of decision rule threshold.
Thus, a ROC curve is calculated if an explanatory series is binary.
A ROC curve is plotted by laying off the obtained sensitivity values along the Y axis, and (1 - specificity) along the X axis.
| Property name | Brief description | |
|
Area | The Area property returns curve area. |
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ConfidenceIntervalLower | The ConfidenceIntervalLower property returns lower limit of asymptotic confidence interval of curve area. |
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ConfidenceIntervalUpper | The ConfidenceIntervalUpper property returns upper limit of asymptotic confidence interval of curve area. |
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ConfidenceLevel | The ConfidenceLevel property determines significance of confidence limits. |
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CutOffPoints | The CutOffPoints property returns cutoff threshold values. |
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OneMinusSpecificity | The OneMinusSpecificity property returns value 1 - specificity. |
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Sensitivity | The Sensitivity property returns values of sensitivity. |
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StdError | The StdError property returns standard error of curve area. |
See also: