CHAPTER 2
Traditional Methods
of Anomaly Detection
In this chapter, you will learn about traditional methods of anomaly detection. You
will also learn how various statistical methods and machine learning algorithms work
and how they can be used to detect anomalies and how you can implement anomaly
detection using several algorithms.
In a nutshell, the following topics will be covered throughout this chapter:
• A data science review
• The three styles of anomaly detection
• The isolation forest
• One-class support vector machine (OC-SVM)
Data Science Review
It is important to understand some basic data science concepts in order for you to
evaluate how well your model performs and to compare its performance with other
models.
First of all, the goal in anomaly detection is to determine whether or not a given
point is an anomaly or not. Essentially, you are labeling a data point
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