Encyclopedia of data science and machine learning[electronic resource]

• 其他作者: Wang, John, , IGI Global.
• 出版: Hershey, Pennsylvania : IGI Global 2023.
• 稽核項: 1 online resource (5 volumes (3143 p.)).
• 標題: Machine learning. , Big data. , Data mining. , Electronic books.
• ISBN: 1799892204 , 9781799892205
• 試查全文@TNUA:
  
• 附註: Includes bibliographical references and index. Volume I. Section 1. Accounting analytics. Chapter 1. Auditor change prediction using data mining and audit reports ; Chapter 2. Volatility of semiconductor companies -- Section 2. Approximation methods. Chapter 3. Use of AI in predicting trends in vegetation dynamics in Africa -- Section 3. Autonomous learning systems. Chapter 4. Data science for industry 4.0 -- Section 4. Big data applications. Chapter 5. A patient-centered data-driven analysis of epidural anesthesia ; Chapter 6. Analysis of big data ; Chapter 7. Big data analytics in e-governance and other aspects of society ; Chapter 8. Big data and Islamic finance ; Chapter 9. Big data helps for non-pharmacological disease control measures of COVID-19 ; Chapter 10. Big data mining and analytics with mapreduce ; Chapter 11. Big data technologies and pharmaceutical manufacturing ; Chapter 12. Data warehouse with OLAP technology for the tourism industry ; Chapter 13. Defect detection inmanufacturing via machine learning algorithms ; Chapter 14. Diving into the rabbit hole: understanding delegation of decisions ; Chapter 15. Importance of AI and ML towards smart sensor network utility enhancement ; Chapter 16. Leveraging wi-fi big data streams to support COVID-19 contact tracing ; Chapter 17. Machine learning in the catering industry ; Chapter 18. Speedy management of data using mapreduce approach ; Chapter 19. Storage and query processing architectures forRDF data ; Chapter 20. Virtual singers empowered by machine learning -- Section 5. Big data as a service. Chapter 21. Analyzing U.S. maritime trade and COVID-19 impact using machine learning ; Chapter 22. NEW ARP: data-driven academia resource planning for CAS researchers -- Section 6. Big data systems and tools. Chapter 23. A meta-analytical review of deep learning prediction models for big data ; Chapter 24. Cluster analysis as a decision-making tool ; Chapter 25. Data lakes; Chapter 26. Datafied modelling of self-disclosure in online health communication ; Trust management mechanism in blockchain data science ; Chapter 107. Using machine learning to extract insights from consumer data -- Section 22. Ensemble learning. Chapter 108. Effective bankruptcy prediction models for North American companies ; Chapter 109. Ensemble methods and their applications ; Chapter 110. How to structure data for humanitarian learning ; Chapter 111. Stock price prediction: fuzzy clustering-based approach -- Section 23. Feature engineering. Chapter 112. A hybridized GA-based feature selection for text sentiment analysis -- Volume IV. Chapter 113. Bio-inspired algorithms for feature selection: a brief state of the art -- Section 24. Financial services analytics. Chapter 114. Financial analytics with big data ; Chapter 115. Portfolio optimization for the Indian stock market ; Chapter 116. Product offer and pricing personalization in retail banking -- Section 25. Fuzzy logic and soft computing. Chapter 117. Data hierarchies for generalization of imprecise data ; Chapter 118. Fuzzy complex system of linear equations ; Chapter 119. Fuzzy logic-based classification and authentication of beverages -- Section 26. Gradient-boosting decision trees. Chapter 120. Aircraft maintenance prediction tree algorithms -- Section 27. Graph learning. Chapter 121. Graph data management, modeling, and mining -- Section 28. High-throughput data analysis. Chapter 122. Best practices of feature selection in multi-omics data ; Chapter 123. Class discovery, comparison, and prediction methods for RNA-seq data -- Section 29. Industry 4.0. Chapter 124. AI is transforming insurance with five emerging business models ; Chapter 125. Artificial intelligence, big data, and machine learning in industry 4.0 ; Chapter 126. Big data and sustainability innovation ; Chapter 127. Deep learning for cyber security risk assessment in iiot systems ; Chapter 128. Digital transformation and circular economy for sustainability ; Chapter 129. Emerging new technologies and industrial revol
• 摘要: "This book examines current, state-of-the-art research in the areas of data science, machine learning, data mining, optimization, artificial intelligence, statistics, and the interactions, linkages, and applications of knowledge-based business with information systems"--
• 電子資源: https://dbs.tnua.edu.tw/login?url=http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-9220-5
• 系統號: 005331149
• 資料類型: 電子書
• 讀者標籤: 需登入
• 引用網址: 複製連結
• 目前引用數