Anomaly Detection Using Isolation Forest in Python
From bank fraud to preventative machine maintenance, anomaly detection is an incredibly useful and common application of machine learning. The isolation forest algorithm is a simple yet powerful choice to accomplish this task. In this article we'll cover: An Introduction to Anomaly Detection Use Cases of Anomaly Detection What Is Isolation Forest? Using Isolation Forest for Anomaly Detection Implementation in Python Introduction to Anomaly Detection An outlier is nothing but a data point that differs significantly from other data points in the given dataset. Anomaly detection is the process of finding the outliers in the data, i.e. points that are significantly different from the majority of the other data points. Large, real-world datasets may have very complicated patterns that are difficult to detect by just looking at the data. That's why the study of anomaly detection is an extremely important application of Machine Learning. In this article we are going to implement
