The book is an unstructured data mining quest, which takes the reader through different features of unstructured data mining while unfolding the practical facets of Big Data. It emphasizes more on machine learning and mining methods required for processing and decision-making. The text begins with the introduction to the subject and explores the concept of data mining methods and models along with the applications. It then goes into detail on other aspects of Big Data analytics, such as clustering, incremental learning, multi-label association and knowledge representation. The readers are also made familiar with business analytics to create value. The book finally ends with a discussion on the areas where research can be explored.
The book is designed for the senior level undergraduate, and postgraduate students of computer science and engineering.
Here Is A Preview Of What Inside The Book:
- Big data
- Statistics in practice
- Descriptive and Inferential Statistics
- Parameters and Statistics
- Statistical data analysis
- Variables
- SUMMARY OF THE GENERAL METHOD OF DECISION ANALYSIS
- ANOTHER DECISION TREE MODEL AND ITS ANALYSIS
- Making Data Work for You
- Predictive Modeling Techniques
