TY - GEN
T1 - Comparative Analysis of Generic Outlier Detection Techniques
AU - Vasudev, Kini T.
AU - Manohara Pai, M. M.
AU - Pai, Radhika M.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - An anomaly, also known as an outlier, is an event that deviates from the norm and raises suspicion. Such anomalies are found by a procedure called anomaly detection. Every anomaly is a potential threat to the robustness and security of the system, which is why anomaly detection is critical. In this proposed research work, anomaly detection algorithms are implemented to isolate outliers from cured input data. The comparative analysis of the algorithms demonstrates that the Isolation Forest performs better than Gaussian Mixture Model (GMM) and k-Nearest Neighbour (kNN) algorithms.
AB - An anomaly, also known as an outlier, is an event that deviates from the norm and raises suspicion. Such anomalies are found by a procedure called anomaly detection. Every anomaly is a potential threat to the robustness and security of the system, which is why anomaly detection is critical. In this proposed research work, anomaly detection algorithms are implemented to isolate outliers from cured input data. The comparative analysis of the algorithms demonstrates that the Isolation Forest performs better than Gaussian Mixture Model (GMM) and k-Nearest Neighbour (kNN) algorithms.
UR - http://www.scopus.com/inward/record.url?scp=85187721525&partnerID=8YFLogxK
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U2 - 10.1007/978-981-99-6346-1_10
DO - 10.1007/978-981-99-6346-1_10
M3 - Conference contribution
AN - SCOPUS:85187721525
SN - 9789819963454
T3 - Lecture Notes in Networks and Systems
SP - 117
EP - 126
BT - Data Analytics and Learning - Proceedings of DAL 2022
A2 - Guru, D.S.
A2 - Kumar, N. Vinay
A2 - Javed, Mohammed
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Data Analytics and Learning, DAL 2022
Y2 - 30 December 2022 through 31 December 2022
ER -