Home › Entities › academia › Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques

Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques

Research article (2024 IEEE 9th International Conference for Convergence in Technology (I2CT), 2024) · cited 14× · AI/ML
academia openalex:W4399486458
Press Enter · cited answer in seconds

Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques

Summary

Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques is a scholarly article[1].

Key Facts

  • Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques. Retrieved May 24, 2026, from https://4ort.xyz/entity/interpretable-anomaly-detection-a-hybrid-approach-using-rule-based-and-machine-learning-techniques
MLA “Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/interpretable-anomaly-detection-a-hybrid-approach-using-rule-based-and-machine-learning-techniques.
BibTeX @misc{4ortxyz_interpretable-anomaly-detection-a-hybrid-approach-using-rule-based-and-machine-learning-techniques_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques}}, year = {2026}, url = {https://4ort.xyz/entity/interpretable-anomaly-detection-a-hybrid-approach-using-rule-based-and-machine-learning-techniques}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Interpretable Anomaly Detection: A Hybrid Approach Using Rule-Based and Machine Learning Techniques — https://4ort.xyz/entity/interpretable-anomaly-detection-a-hybrid-approach-using-rule-based-and-machine-learning-techniques (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/interpretable-anomaly-detection-a-hybrid-approach-using-rule-based-and-machine-learning-techniques · Last refreshed: