Nomenclature Of Datastreams Mining Strategies Concept Drift And Research Objectives
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Nomenclature of Datastreams, Mining Strategies, Concept Drift and Research Objectives
Author: Dr. Annaluri Sreenivasa Rao
language: en
Publisher: Shineeks Publishers
Release Date: 2022-03-16
Streaming data is one of the primary sources of what is known as big data. While data streams and big data have gotten a lot of attention in the recent decade, many research methodologies are often intended for well-behaved controlled problem settings, overlooking major obstacles given by real-world applications. The eight open difficulties for data stream mining are discussed in this book. Our goal is to discover gaps between present research and useful applications, to highlight unresolved issues, and to create new data stream mining research lines that are relevant to applications.
Intelligent Computing for Sustainable Development
The two-volume proceedings set CCIS 2121 and 2122 constitutes the refereed proceedings of the First International Conference on Intelligent Computing for Sustainable Development, ICICSD 2023, which took place in Hyderabad, India, during August 25–26, 2023. The 46 papers included in these proceedings were carefully reviewed and selected from 138 submissions. They focus on digital healthcare, renewable energy, smart cities, digital farming, and autonomous systems.
Machine Learning Techniques for Improved Business Analytics
Analytical tools and algorithms are essential in business data and information systems. Efficient economic and financial forecasting in machine learning techniques increases gains while reducing risks. Providing research on predictive models with high accuracy, stability, and ease of interpretation is important in improving data preparation, analysis, and implementation processes in business organizations. Machine Learning Techniques for Improved Business Analytics is a collection of innovative research on the methods and applications of artificial intelligence in strategic business decisions and management. Featuring coverage on a broad range of topics such as data mining, portfolio optimization, and social network analysis, this book is ideally designed for business managers and practitioners, upper-level business students, and researchers seeking current research on large-scale information control and evaluation technologies that exceed the functionality of conventional data processing techniques.