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This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6–8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in…mehr
This book offers a systematic overview of the concepts and practical techniques that readers need to get the most out of their large-scale data mining projects and research studies. It guides them through the data-analytical thinking essential to extract useful information and obtain commercial value from the data. Presenting the outcomes of International Conference on Soft Computing and Data Mining (SCDM-2017), held in Johor, Malaysia on February 6–8, 2018, it provides a well-balanced integration of soft computing and data mining techniques. The two constituents are brought together in various combinations of applications and practices. To thrive in these data-driven ecosystems, researchers, engineers, data analysts, practitioners, and managers must understand the design choice and options of soft computing and data mining techniques, and as such this book is a valuable resource, helping readers solve complex benchmark problems and better appreciate the concepts, tools, and techniquesemployed.
An Improved Hybrid Firefly Algorithm for Solving Optimization Problems.- Classification of JPEG Files by Using Extreme Learning Machine.- A Relative Tolerance Relation of Rough Set for Incomplete Information Systems.- An Algorithm Design of Kansei Recommender System.- A Framework to Cluster Temporal Data Using Personalised Modelling Approach.- Fibonacci Polynomials Based Functional Link Neural Network for Classification Tasks.
An Improved Hybrid Firefly Algorithm for Solving Optimization Problems.- Classification of JPEG Files by Using Extreme Learning Machine.- A Relative Tolerance Relation of Rough Set for Incomplete Information Systems.- An Algorithm Design of Kansei Recommender System.- A Framework to Cluster Temporal Data Using Personalised Modelling Approach.- Fibonacci Polynomials Based Functional Link Neural Network for Classification Tasks.
An Improved Hybrid Firefly Algorithm for Solving Optimization Problems.- Classification of JPEG Files by Using Extreme Learning Machine.- A Relative Tolerance Relation of Rough Set for Incomplete Information Systems.- An Algorithm Design of Kansei Recommender System.- A Framework to Cluster Temporal Data Using Personalised Modelling Approach.- Fibonacci Polynomials Based Functional Link Neural Network for Classification Tasks.
An Improved Hybrid Firefly Algorithm for Solving Optimization Problems.- Classification of JPEG Files by Using Extreme Learning Machine.- A Relative Tolerance Relation of Rough Set for Incomplete Information Systems.- An Algorithm Design of Kansei Recommender System.- A Framework to Cluster Temporal Data Using Personalised Modelling Approach.- Fibonacci Polynomials Based Functional Link Neural Network for Classification Tasks.
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