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)

Anomalous pattern detection

The second approach uses the pattern library in an inverse fashion, meaning that the library encodes only the positive patterns, which are marked with green plus signs in the following diagram. When an observed behavior (the blue circle) cannot be matched against the library, it is considered anomalous:

This approach requires us to model only what we have seen in the past, that is, normal patterns. If we return to the doctor example, the main reason that we visited the doctor in the first place was because we did not feel well. Our perceived state of feelings (for example, a headache and sore skin) did not match our usual feelings, and therefore, we decided to seek a doctor. We don't know which disease caused this state, nor do we know the treatment, but we were able to observe that it doesn't match the usual state.

A major advantage of this...