Local Outlier Factor for Anomaly Detection

Anomaly detection is an important application used across various verticals like healthcare, finance, manufacturing and so on. Local Outlier Factor is a popular density based technique for anomaly detection that does not require prior examples of anomalies. What are Advantages of LOF for Anomaly Detection? One of the main challenges with Anomaly detection is the…

What are Isolation Forests? How to use them for Anomaly Detection?

All of us know random forests, one of the most popular ML models. They are a supervised learning algorithm, used in a wide variety of applications for classification and regression. Can we use random forests in an unsupervised setting? (where we have no labeled data?) Isolation forests are a variation of random forests that can…