The results of numerical experiments carried using 27 various datasets and reported in this paper lead us to the conclusion that FCM can play a pivotal role in an enhancement of Isolation Forest approach and raises up the values of particular measures of effectiveness of the anomaly detection ...
We propose innovative score evaluation function for MSTBIF method.We introduce fuzzy rules in the Takagi-Sugeno model for score evaluation.The proposed solution has been tested on 26 real world datasets.The results of MSTBIF-TS indicate its high effectiveness in anomaly detection.关键词: Anomaly de...
The local outlier score depends on the degree of isolation of the object with respect to its surrounding neighborhood. Local outlier detection has better results for data sets with different density clusters. The disadvantage is the method is very sensitive to the parameters defining the neighborhood...
Paper [31] introduces the Isolation Forest (iForest) method which is an unsupervised anomaly detection algorithm that represents features as tree structures. Paper [32] describes a cluster approach for detecting log anomalies. The DeepLog method is proposed in paper [7]. This method is a recurren...