AnomalyDetector
is an option for functions such as Classify that specifies an anomaly detector for them to include.
Details
- Possible settings for AnomalyDetector include:
-
None use no anomaly detector (default) AnomalyDetectorFunction[…] use the specified anomaly detector Automatic create an anomaly detector from the available data LearnedDistribution[…] create an anomaly detector from a learned distribution - The specified anomaly detector is typically used during model evaluation, not during model training.
- When an anomalous example is encountered, Missing["Anomalous"] is returned instead of a classification or prediction result.
- Classify[ClassifierFunction[…],AnomalyDetectordetector] can be used to overwrite the anomaly detector of a particular classifier (and similarly for PredictorFunction[…]).
- Classify[ClassifierFunction[…],AcceptanceThresholdt] can be used to overwrite the value of the rarer-probability threshold used by the anomaly detector.
- ClassifierFunction[…][example,AnomalyDetectordetector] can be used to temporarily overwrite the anomaly detector during a model evaluation.
- ClassifierFunction[…][example,AcceptanceThresholdt] can be used to temporarily overwrite the rarer-probability threshold value during a model evaluation.
Examples
Basic Examples (3)
Create a classifier and specify that an anomaly detector should be included:
Evaluate the classifier on a non-anomalous input:
Evaluate the classifier on an anomalous input:
The "Probabilities" property is not affected by the anomaly detector:
Remove the anomaly detector from the classifier:
Create a classifier without an anomaly detector:
Train an anomaly detector from the training inputs:
Add the anomaly detector to the classifier:
Change the value of the acceptance threshold when evaluating the classifier:
Create a predictor and specify that an anomaly detector should be included:
Evaluate the predictor on a non-anomalous input:
Evaluate the predictor on an anomalous input:
The "Distribution" property is not affected by the anomaly detector:
Change the value of the acceptance threshold when evaluating the predictor:
Text
Wolfram Research (2020), AnomalyDetector, Wolfram Language function, https://reference.wolfram.com/language/ref/AnomalyDetector.html.
CMS
Wolfram Language. 2020. "AnomalyDetector." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/AnomalyDetector.html.
APA
Wolfram Language. (2020). AnomalyDetector. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/AnomalyDetector.html