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It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis.
This book is mainly about an innovative and fundamental method called "intelligent knowledge" to bridge the gap between data mining and knowledge management, two important fields recognized by the information technology (IT) community and business analytics (BA) community respectively.
Optimization techniques have been widely adopted to implement various data mining algorithms. This book focuses on cutting-edge theoretical developments and real-life applications in optimization, covering a range of fields from finance to bioinformatics.
When we learn from books or daily experience, we make associations and draw inferences on the basis of information that is insufficient for under standing.
This book examines issues of PCM, including consistency test, inconsistent data identification and adjustment, missing or uncertain data estimation, and sensitivity analysis of rank reversal. Proposes and demonstrates an induced bias matrix model (IBMM).
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