Anomaly detection

In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.

单词	Anomaly detection
释义	Anomaly detection 英语例句库 Focus on design and implementation of K-Means-based anomaly detection algorithm engine and cluster analysis module, as well as the Apriori algorithm based on correlation analyzer. 重点设计和实现了基于K-Means 算法的异常检测引擎和聚类分析模块，以及基于Apriori 算法的关联分析器。英语百科 Anomaly detection In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text. Anomalies are also referred to as outliers, novelties, noise, deviations and exceptions.
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