Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms

✍ Scribed by Veljko Milutinovic, Nenad Mitic, Aleksandar Kartelj, Milos Kotlar

• Publisher: IGI Global
• Year: 2022
• Tongue: English
• Leaves: 306
• Series: Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC)
• Edition: 1
• Category: Library

✦ Synopsis

Based on current literature and cutting-edge advances in the machine learning field, there are four algorithms whose usage in new application domains must be explored: neural networks, rule induction algorithms, tree-based algorithms, and density-based algorithms. A number of machine learning related algorithms have been derived from these four algorithms. Consequently, they represent excellent underlying methods for extracting hidden knowledge from unstructured data, as essential data mining tasks.

Implementation of Machine Learning Algorithms Using Control-Flow and Dataflow Paradigms presents widely used data-mining algorithms and explains their advantages and disadvantages, their mathematical treatment, applications, energy efficient implementations, and more. It presents research of energy efficient accelerators for machine learning algorithms. Covering topics such as control-flow implementation, approximate computing, and decision tree algorithms, this book is an essential resource for computer scientists, engineers, students and educators of higher education, researchers, and academicians.

✦ Table of Contents

Cover
Title Page
Copyright Page
Book Series
Table of Contents
Preface
Introduction
Chapter 1: Introduction to Data Mining
Chapter 2: Classification Algorithms and Control-Flow Implementation
Chapter 3: Classification Algorithms and Dataflow Implementation
Chapter 4: Scientific Applications of Machine Learning Algorithms
Chapter 5: Business and Industrial Applications of Machine Learning Algorithms
Chapter 6: Implementation Details of Neural Networks Using Dataflow
Chapter 7: Implementation Details of Decision Tree Algorithms Using Dataflow
Chapter 8: Implementation Details of Rule-Based Algorithms Using Dataflow
Chapter 9: Implementation Details of Density-Based Algorithms Using Dataflow
Chapter 10: Issues Related to Acceleration of Algorithms
Conclusion
Glossary
Related Readings
About the Authors
Index

✦ Subjects

Machine Learning