Book Image

Machine Learning in Java - Second Edition

By : AshishSingh Bhatia, Bostjan Kaluza
Book Image

Machine Learning in Java - Second Edition

By: AshishSingh Bhatia, Bostjan Kaluza

Overview of this book

As the amount of data in the world continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of big data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need. You will start by learning how to apply machine learning methods to a variety of common tasks including classification, prediction, forecasting, market basket analysis, and clustering. The code in this book works for JDK 8 and above, the code is tested on JDK 11. Moving on, you will discover how to detect anomalies and fraud, and ways to perform activity recognition, image recognition, and text analysis. By the end of the book, you will have explored related web resources and technologies that will help you take your learning to the next level. By applying the most effective machine learning methods to real-world problems, you will gain hands-on experience that will transform the way you think about data.
Table of Contents (13 chapters)

Anomaly detection in website traffic

In the second example, we'll focus on modeling the opposite of the previous example. Instead of discussing what typical fraudless cases are, we'll discuss the normal expected behavior of the system. If something cannot be matched against our expected model, it will be considered anomalous.

Dataset

We'll work with a publicly available dataset that was released by Yahoo! Labs, which is useful for discussing how to detect anomalies in time series data. For Yahoo, the main use case is in detecting unusual traffic on Yahoo servers.

Even though Yahoo has announced that their data is publicly available, you have to apply to use it, and it takes about 24 hours before the approval...