Anomaly Detection with Isolation Forest and Kernel Density Estimation

Anomaly detection is to find data points that deviate from the norm. In other words, those are the points that do not follow expected patterns. Outliers and exceptions are terms used to describe unusual data. Anomaly detection is important in a variety of fields because it gives valuable and actionable insights. An abnormality in an … Continue reading Anomaly Detection with Isolation Forest and Kernel Density Estimation