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http://archive.cmb.ac.lk:8080/xmlui/handle/70130/7462Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dissanayake, D.M. | - |
| dc.contributor.author | Navarathna, R. | - |
| dc.contributor.author | Viswakula, S. | - |
| dc.date.accessioned | 2024-12-09T05:25:47Z | - |
| dc.date.available | 2024-12-09T05:25:47Z | - |
| dc.date.issued | 2024 | - |
| dc.identifier.citation | Dissanayake, D.M., Navarathna, R., and Viswakula, S. (2024). Violation-based Feature Selection for Isolation Forest. Proceedings: University of Colombo Annual Research Symposium 2024, p.298. | en_US |
| dc.identifier.uri | http://archive.cmb.ac.lk:8080/xmlui/handle/70130/7462 | - |
| dc.description.abstract | Anomaly detection is crucial in sectors like finance and healthcare to identify deviations from normal behavior. The Isolation Forest (ISF) algorithm, introduced by Liu et al. (2008), is effective but has limitations, such as bias towards correlated variables and suboptimal results with irrelevant features. This study introduces the Violation Features Based Isolation Forest (VFIF) algorithm, ... | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | University of Colombo | en_US |
| dc.subject | Isolation Forest | en_US |
| dc.subject | Anomaly Detection | en_US |
| dc.subject | Rule Violation | en_US |
| dc.title | Violation-based Feature Selection for Isolation Forest | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Department of Statistics | |
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