April 12, 2022, 9:55 a.m. | Seungjun (Josh) Kim

Towards Data Science - Medium towardsdatascience.com

Outlier detection is crucial—especially for data quality assessment

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Introduction

Outlier Detection is crucial in many different ways. If a company wants to understand anomalous / atypical customer behavior, it needs to first identify such customers. Outlier Detection techniques come into play in this case. Outlier Detection is also very useful for vetting data quality of a dataset. Here, we look at three mainstream approaches that are frequently used to detect outliers.

IQR / Standard …

anomaly detection clustering detection getting-started go machine learning outlier-detection

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