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Self-supervised Isolation Forest/Evidence
Method evidence record

Self-supervised Isolation Forest

Self-supervised Isolation Forest augments the classic Isolation Forest anomaly detector with a self-supervised pre-training stage. A pretext task — such as predicting rotation, masked features, or contrastive pairs — is solved without labels to learn a richer feature representation, which is then used when building the isolation trees, yielding sharper anomaly scores on complex, high-dimensional tabular data.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Self-supervised Isolation Forest (SSL-augmented Anomaly Detection)
Taxonomic method record · ml-model / machine-learning
  • Liu, F. T., Ting, K. M., & Zhou, Z.-H. (2008). Isolation Forest. In Proceedings of the 8th IEEE International Conference on Data Mining (ICDM), pp. 413–422. · DOI 10.1109/ICDM.2008.17
  • Isolation Forest. Wikipedia. · URL
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Related methods

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Same method familyAutoencodermachine-suggested · Relational suggestion, not evidence.Same method familyIsolation Forestmachine-suggested · Relational suggestion, not evidence.Same method familyLocal Outlier Factormachine-suggested · Relational suggestion, not evidence.Taxonomic bucketOne-class SVMmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

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Sources

2 recorded citations, copied from the method source record.

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