• Handbook of research on automated feature engineering and advanced applications in data science[electronic resource] /
  • 紀錄類型: 書目-電子資源 : Monograph/item
    杜威分類號: 006.3/12
    書名/作者: Handbook of research on automated feature engineering and advanced applications in data science/ Mrutyunjaya Panda and Harekrishna Misra, editors.
    其他作者: Panda, Mrutyunjaya.
    出版者: Hershey, Pennsylvania : : IGI Global,, 2021.
    面頁冊數: 1 online resource (xxviii, 392 p.)
    標題: Data mining.
    標題: Big data - Industrial applications.
    標題: Automatic data collection systems.
    標題: Automatic classification.
    ISBN: 9781799866619 (ebk.)
    ISBN: 9781799866596 (hbk.)
    ISBN: 9781799866602 (pbk.)
    書目註: Includes bibliographical references and index.
    內容註: Chapter 1. Feature engineering for various data types in data science -- Chapter 2. Feature selection techniques in high dimensional data with machine learning and deep learning -- Chapter 3. Hybrid attributes technique filter for the tracking of crowd behavior -- Chapter 4. Useful features for computer-aided diagnosis systems for melanoma detection using dermoscopic images -- Chapter 5. Development of rainfall prediction models using machine learning approaches for different agro-climatic zones -- Chapter 6. Multi-feature fusion and machine learning: a model for early detection of freezing of gait events in patients with Parkinson's disease -- Chapter 7. Developing brain tumor detection model using deep feature extraction via transfer learning -- Chapter 8. Feature engineering for structural health monitoring (SHM): a damage characterization review -- Chapter 9. Speech enhancement using neuro-fuzzy classifier -- Chapter 10. Applications of feature engineering techniques for text data -- Chapter 11. Deep learning for feature engineering-based improved weather prediction: a predictive modeling -- Chapter 12. Computationally efficient and effective machine learning model using time series data in different prediction problems -- Chapter 13. Machine learning and convolution neural network approaches to plant leaf recognition -- Chapter 14. Reciprocation of Indian States on trade relation -- Chapter 15. Performance evaluation of machine learning techniques for customer churn prediction in telecommunication sector -- Chapter 16. Efficient software reliability prediction with evolutionary virtual data position exploration -- Chapter 17. Secure chaotic image encryption based on multi-point row-column-crossover operation -- Chapter 18. Machine automation making cyber-policy violator more resilient: a proportionate study.
    摘要、提要註: "This edited book will start with an introduction to feature engineering and then move onto recent concepts, methods and applications with the use of various data types that includes : text, image, streaming data, social network data, financial data, biomedical data, bioinformatics etc. to help readers gain insight into how features can be extracted and transformed from raw data"--
    電子資源: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-6659-6
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