Question

After performing anomaly detection, data miner A wants to find clusters of outliers. Data miner B claims that this does not make any sense and suggests that A re-read the definition of an anomaly. Do you think it is meaningful to cluster anomalies? Explain.

Answer 1

find clusters of outliers, it may be possible because depending on the number of data points and the impact of the study The later ismeans that depending on the budget, datasetand timely constraints of the project, it is essential to move on with the cluster anomalies.

Before proceeding towards the conclusion ofa data mining problem we need to keep twothings is mind; first there is no one site fits all solution for a data science problem and garbage in is equal to garbage out. The former means that if data miner A wants to find clusters of outliers, it may be

One of the studies [TR CS] suggest that outward anonymity, and wide prevalenceof saving sensitive information on computershas attracted a large number of criminals andhacker hobbyists. This has resulted in an overwhelming increase in attacks from outliervulnerabilities and raised recent interest in

significant deviations from the model are flagged anomalous. More inference can be done based on the training data and the steps involved in the data cleaning processes as outlier detectionis vital during that stage.

More inference can be done based on the training data and the steps involved in thedata cleaning processes as outlier detectionis vital during that stage References TR CS] Muhammad H. Arshad and Philip KChan : ldentifying Outliers via Clustering forAnomaly Detection, 2003-19
thank you