Artificial Intelligence in Data Mining
Theories and Applications

Offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications

D. Binu (Edited by), B.R. Rajakumar (Edited by)

9780128206010, Elsevier Science

Paperback, published 22 February 2021

270 pages
23.4 x 19 x 1.8 cm, 0.57 kg

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area.

1. Introduction 2. Intelligence Methods for Data Mining Tasks 3. Unsupervised Learning Methods for Data Clustering 4. Heuristic Methods for Data Clustering 5. Deep Learning Methods for Data Classification 6. Neural Networks for Data Classification 7. Application of Artificial Intelligence in the Perspective of Data Mining 8. Biomedical Data Mining for Improved Clinical Diagnosis 9. Satellite Data: Big Data Extraction and Analysis 10. Advancement of Data Mining Methods for Improvement of Agricultural Methods and Productivity 11. Advanced Data Mining for Defense and Security Applications

Subject Areas: Biomedical engineering [MQW]