Objective

After reading this chapter, you will be able to apply some of the techniques to identify any anomaly in data, and you will have a general understanding of how and where anomaly detection algorithms can be useful. All code is available at https://gist.github.com/sudipto80/e599ab069981736ffa1d.

Different classification algorithms

The following algorithms will be discussed in this chapter:

• Statistical anomaly detection

• Nearest neighbor based anomaly detection

• Density estimation based anomaly detection

Some cool things you will do

With the techniques learned from this chapter, you will be able to spot lies. You will also have a deeper understanding of how fraudulent behaviors on credit cards are found.

The different types of anomalies

Anomalies can be classified into any of the following categories:

• Point anomalies

• Contextual anomalies

• Collective anomalies

We will go through each one of them in detail:

• Point anomalies: If an individual data instance can be considered as anomalous with respect...