This book seeks to familiarize students with the fundamental concepts and techniques used in the field of data mining. The content spans a wide range of topics including data preprocessing, classification, clustering, association analysis, and anomaly detection. By combining theoretical insights with practical examples, the book aims to equip students with the skills necessary to extract meaningful patterns and knowledge from large datasets, thus preparing them for challenges in data-driven industries.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Produkt-Hinweis
Maße
Höhe: 254 mm
Breite: 203 mm
ISBN-13
978-1-77956-302-6 (9781779563026)
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Schweitzer Klassifikation
Bechoo Lal, PhD. became a Member (M) of IAENG: International Association of Engineers, USA with membership (108820) in 2010, a Senior Member (SM) in 2019. He has a doctorate PhD in Computer Science, PhD- Information System from University of Mumbai, Master from Banaras Hindu University (BHU), PGP- Data Science from Purdue University, USA. Currently working as a Associate Professor in Department of Computer Science & Engineering, KLEF- KL University Vijayawada Campus Andhra Pradesh, India. His research areas are data science, big data analytics and Machine Learning.
Introduction To Data Mining
2 Data
3 Exploring Data
4 Classification: Basic Concepts, Decision Trees, And Model Evaluation
5 Alternative Techniques
6 Association Analysis: Basic Concepts And Algorithms
7 Association Analysis: Advanced Concepts
8 Cluster Analysis: Basic Concepts And Algorithms
9 Cluster Analysis: Additional Issues And Algorithms
10 Anomaly Detection
