Outlier (Anomaly) Detection Modelling in PMML
نویسندگان
چکیده
PMML is an industry-standard XML-based open format for representing statistical and data mining models. Since PMML does not yet support outlier (anomaly) detection, in this paper we propose a new outlier detection model to foster interoperability in this emerging field. Our proposal is included in the PMML RoadMap for PMML 4.4. We demonstrate the proposed format on one supervised and two unsupervised outlier detection approaches: association rule-based classifier CBA, frequent-pattern based method FPOF and isolation forests.
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