Intelligent Data Analysis

Preface

Intelligent data analysis (IDA), knowledge discovery, and decision support have recently become more challenging research fields and have gained much attention among a large number of researchers and practitioners. In our view, the awareness of these challenging research fields and emerging technologies among the research community will increase the applications in biomedical science. This book aims to present the various approaches, techniques, and methods that are available for IDA, and to present case studies of their application.

This volume comprises 18 chapters focusing on the latest advances in IDA tools and techniques.

Machine learning models are broadly categorized into two types: white box and black box. Due to the difficulty in interpreting their inner workings, some machine learning models are considered black box models. Chapter 1 focuses on the different machine learning models, along with their advantages and limitations as far as the analysis of data is concerned.

With the advancement of technology, the amount of data generated is very large. The data generated has useful information that needs to be gathered by data analytics tools in order to make better decisions. In Chapter 2, the definition of data and its classifications based on different factors is given. The reader will learn about how and what data is and about the breakup of the data. After a description of what data is, the chapter will focus on defining and explaining big data and the various ...