Last updated on August 1, 2020. I am continuously updating this post. In data mining, anomaly detection (also outlier detection) is the identification of rare items.
In data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. — [Wikipedia_](https://en.wikipedia.org/wiki/Anomaly_detection)._
This post contents:
Outlier Analysis by Charu C. Aggarwal.
Outlier Ensembles by Charu C. Aggarwal, Saket Sathe.
Learn different Machine Learning-Based Approaches for Anomaly Detection and how to apply on the dataset to solve a problem.
Reviewing challenges, methods and opportunities in deep anomaly detection. This post summarizes a comprehensive survey paper on deep learning for anomaly detection .
Credit Card Fraud Detection via Machine Learning: A Case Study. A machine learning guide on how to identify fraudulent credit card transactions by using the PyOD toolkit.
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