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Descripción

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.

  • Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering
  • Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks
  • Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense

1. 1. Introduction - p. 1 2. 2. Intelligence methods for data mining task - p. 21 3. 3. Unsupervised learning methods for data clustering - p. 41 4. 4. Heuristic methods for data clustering - p. 65 5. 5. Deep learning methods for data classification - p. 87 6. 6. Neural networks for data classification - p. 109 7. 7. Application of artificial intelligence in the perspective of data mining - p. 133 8. 8. Biomedical data mining for improved clinical diagnosis - p. 155 9. 9. Satellite data: big data extraction and analysis - p. 177 10. 10. Advancement of data mining methods for improvement of agricultural methods and productivity - p. 199 11. 11. Advanced data mining for defense and security applications - p. 223 12. Index - p. 243

Descripcion
Descripción

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.

  • Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering
  • Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks
  • Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense

1. 1. Introduction - p. 1 2. 2. Intelligence methods for data mining task - p. 21 3. 3. Unsupervised learning methods for data clustering - p. 41 4. 4. Heuristic methods for data clustering - p. 65 5. 5. Deep learning methods for data classification - p. 87 6. 6. Neural networks for data classification - p. 109 7. 7. Application of artificial intelligence in the perspective of data mining - p. 133 8. 8. Biomedical data mining for improved clinical diagnosis - p. 155 9. 9. Satellite data: big data extraction and analysis - p. 177 10. 10. Advancement of data mining methods for improvement of agricultural methods and productivity - p. 199 11. 11. Advanced data mining for defense and security applications - p. 223 12. Index - p. 243

Indice
Autores
Muestra
Ficha Técnica