Advances in Data Mining and Intelligent Analytics - Methods, Interpretability, and Cross-Domain Applications

Andries Engelbrecht

ISBN 10: 1836342691 / ISBN 13: 9781836342694

Published by Intechopen Apr 2026, 2026

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -In an era defined by data-driven decision-making, the ability to extract meaningful knowledge from complex datasets is more important than ever. Advances in Data Mining and Intelligent Analytics - Methods, Interpretability, and Cross-Domain Applications offers a timely and focused exploration of how modern data mining supports discovery, prediction, and intelligent decision-making across diverse domains. This volume brings together key ideas spanning data visualization, statistical thinking, machine learning, deep learning, and scalable data management, presenting a coherent view of both foundational principles and emerging directions. Readers are introduced to concepts such as exploratory data analysis, predictive modeling, model optimization, adversarial learning, interpretable AI, and data infrastructure for large-scale applications. Emphasizing real-world relevance, the book highlights how data mining can be applied across healthcare, agriculture, industry, and intelligent digital systems. Designed for graduate students, researchers, and professionals, the text balances conceptual understanding with a practical perspective, making it suitable as both a reference and a learning resource. Key advantages of this book include its integration of foundational knowledge with advanced methods, its cross-domain applicability, and its focus on scalable and responsible data use. By connecting core data mining techniques with current AI-driven approaches, this volume helps readers understand not only how methods work but also why they matter in today's data-rich world. Whether the goal is to strengthen analytical skills, explore modern machine learning strategies, or understand the evolving landscape of intelligent data analysis, this book provides a clear and engaging guide to the field. 196 pp. Englisch.

Seller Inventory # 9781836342694

Bibliographic Details

• Title: Advances in Data Mining and Intelligent Analytics - Methods, Interpretability, and Cross-Domain Applications
• Publisher: Intechopen Apr 2026
• Publication Date: 2026
• Language: English
• ISBN 10: 1836342691
• ISBN 13: 9781836342694
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 18D millimeters 260 millimeters width by 183 millimeters height by 18 millimeters depth
• Weight: 619 grams

About this title

Synopsis

In an era defined by data-driven decision-making, the ability to extract meaningful knowledge from complex datasets is more important than ever. Advances in Data Mining and Intelligent Analytics - Methods, Interpretability, and Cross-Domain Applications offers a timely and focused exploration of how modern data mining supports discovery, prediction, and intelligent decision-making across diverse domains. This volume brings together key ideas spanning data visualization, statistical thinking, machine learning, deep learning, and scalable data management, presenting a coherent view of both foundational principles and emerging directions. Readers are introduced to concepts such as exploratory data analysis, predictive modeling, model optimization, adversarial learning, interpretable AI, and data infrastructure for large-scale applications. Emphasizing real-world relevance, the book highlights how data mining can be applied across healthcare, agriculture, industry, and intelligent digital systems. Designed for graduate students, researchers, and professionals, the text balances conceptual understanding with a practical perspective, making it suitable as both a reference and a learning resource. Key advantages of this book include its integration of foundational knowledge with advanced methods, its cross-domain applicability, and its focus on scalable and responsible data use. By connecting core data mining techniques with current AI-driven approaches, this volume helps readers understand not only how methods work but also why they matter in today’s data-rich world. Whether the goal is to strengthen analytical skills, explore modern machine learning strategies, or understand the evolving landscape of intelligent data analysis, this book provides a clear and engaging guide to the field.