@Alias(value={"ComputeROCCurve","de.lmu.ifi.dbs.elki.evaluation.roc.ComputeROCCurve"}) public class OutlierROCCurve extends Object implements Evaluator
-rocauc.positive
specifies the class label of
"positive" hits.
The nested algorithm -algorithm
will be run, the result will be
searched for an iterable or ordering result, which then is compared with the
clustering obtained via the given class label.Modifier and Type | Class and Description |
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static class |
OutlierROCCurve.Parameterizer
Parameterization class.
|
static class |
OutlierROCCurve.ROCResult
Result object for ROC curves.
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Modifier and Type | Field and Description |
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private static Logging |
LOG
The logger.
|
static OptionID |
POSITIVE_CLASS_NAME_ID
The pattern to identify positive classes.
|
private Pattern |
positiveClassName
Stores the "positive" class.
|
static String |
ROCAUC_LABEL
The label we use for marking ROCAUC values.
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Constructor and Description |
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OutlierROCCurve(Pattern positive_class_name)
Constructor.
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Modifier and Type | Method and Description |
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private OutlierROCCurve.ROCResult |
computeROCResult(int size,
SetDBIDs positiveids,
DBIDs order) |
private OutlierROCCurve.ROCResult |
computeROCResult(int size,
SetDBIDs positiveids,
OutlierResult or) |
void |
processNewResult(HierarchicalResult baseResult,
Result result)
Process a result.
|
public static final String ROCAUC_LABEL
private static final Logging LOG
public static final OptionID POSITIVE_CLASS_NAME_ID
Key: -rocauc.positive
private Pattern positiveClassName
public OutlierROCCurve(Pattern positive_class_name)
positive_class_name
- Positive class name patternprivate OutlierROCCurve.ROCResult computeROCResult(int size, SetDBIDs positiveids, DBIDs order)
private OutlierROCCurve.ROCResult computeROCResult(int size, SetDBIDs positiveids, OutlierResult or)
public void processNewResult(HierarchicalResult baseResult, Result result)
ResultProcessor
processNewResult
in interface ResultProcessor
baseResult
- The base of the result tree.result
- Newly added result subtree.