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Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Book Synopsis Computational Methods of Feature Selection by : Huan Liu
Download or read book Computational Methods of Feature Selection written by Huan Liu and published by CRC Press. This book was released on 2007-10-29 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to increasing demands for dimensionality reduction, research on feature selection has deeply and widely expanded into many fields, including computational statistics, pattern recognition, machine learning, data mining, and knowledge discovery. Highlighting current research issues, Computational Methods of Feature Selection introduces the
Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise
Book Synopsis Spectral Feature Selection for Data Mining (Open Access) by : Zheng Alan Zhao
Download or read book Spectral Feature Selection for Data Mining (Open Access) written by Zheng Alan Zhao and published by CRC Press. This book was released on 2011-12-14 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Book Synopsis Encyclopedia of Machine Learning by : Claude Sammut
Download or read book Encyclopedia of Machine Learning written by Claude Sammut and published by Springer Science & Business Media. This book was released on 2011-03-28 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.
Book Synopsis Feature Engineering and Selection by : Max Kuhn
Download or read book Feature Engineering and Selection written by Max Kuhn and published by CRC Press. This book was released on 2019-07-25 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.
This book gathers the refereed proceedings of the Artificial Intelligence and Bioinspired Computational Methods Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Artificial intelligence and bioinspired computational methods now represent crucial areas of computer science research. The topics presented here reflect the current discussion on cutting-edge hybrid and bioinspired algorithms and their applications.
Book Synopsis Artificial Intelligence and Bioinspired Computational Methods by : Radek Silhavy
Download or read book Artificial Intelligence and Bioinspired Computational Methods written by Radek Silhavy and published by Springer Nature. This book was released on 2020-08-08 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the refereed proceedings of the Artificial Intelligence and Bioinspired Computational Methods Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Artificial intelligence and bioinspired computational methods now represent crucial areas of computer science research. The topics presented here reflect the current discussion on cutting-edge hybrid and bioinspired algorithms and their applications.
Book Synopsis Computational Methods to Study Phenotype Evolution and Feature Selection Techniques for Biological Data Under Evolutionary Constraints by : Christina Kratsch
Download or read book Computational Methods to Study Phenotype Evolution and Feature Selection Techniques for Biological Data Under Evolutionary Constraints written by Christina Kratsch and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
This proceedings consists of 20 papers which have been selected and invited from the submissions to the 4th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2016) held on 2-3 May, 2016 in Laxenburg, Austria. The conference is organized into 5 sessions: Advanced Optimization Methods and Their Applications, Models for ICT applications, Topics on discrete mathematics, Data Analytic Methods and Applications and Feature Extractio, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering. The editors hope that this volume can be useful for graduate and Ph.D. students and researchers in Applied Sciences, Computer Science and Applied Mathematics.
Book Synopsis Advanced Computational Methods for Knowledge Engineering by : Thanh Binh Nguyen
Download or read book Advanced Computational Methods for Knowledge Engineering written by Thanh Binh Nguyen and published by Springer. This book was released on 2016-05-01 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings consists of 20 papers which have been selected and invited from the submissions to the 4th International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2016) held on 2-3 May, 2016 in Laxenburg, Austria. The conference is organized into 5 sessions: Advanced Optimization Methods and Their Applications, Models for ICT applications, Topics on discrete mathematics, Data Analytic Methods and Applications and Feature Extractio, respectively. All chapters in the book discuss theoretical and practical issues connected with computational methods and optimization methods for knowledge engineering. The editors hope that this volume can be useful for graduate and Ph.D. students and researchers in Applied Sciences, Computer Science and Applied Mathematics.
This volume contains the extended versions of papers presented at the 3rd International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2015) held on 11-13 May, 2015 in Metz, France. The book contains 5 parts: 1. Mathematical programming and optimization: theory, methods and software, Operational research and decision making, Machine learning, data security, and bioinformatics, Knowledge information system, Software engineering. All chapters in the book discuss theoretical and algorithmic as well as practical issues connected with computation methods & optimization methods for knowledge engineering and machine learning techniques.
Book Synopsis Advanced Computational Methods for Knowledge Engineering by : Hoai An Le Thi
Download or read book Advanced Computational Methods for Knowledge Engineering written by Hoai An Le Thi and published by Springer. This book was released on 2015-05-04 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the extended versions of papers presented at the 3rd International Conference on Computer Science, Applied Mathematics and Applications (ICCSAMA 2015) held on 11-13 May, 2015 in Metz, France. The book contains 5 parts: 1. Mathematical programming and optimization: theory, methods and software, Operational research and decision making, Machine learning, data security, and bioinformatics, Knowledge information system, Software engineering. All chapters in the book discuss theoretical and algorithmic as well as practical issues connected with computation methods & optimization methods for knowledge engineering and machine learning techniques.
Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
Book Synopsis Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms by : Management Association, Information Resources
Download or read book Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms written by Management Association, Information Resources and published by IGI Global. This book was released on 2020-12-05 with total page 1534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic programming is a new and evolutionary method that has become a novel area of research within artificial intelligence known for automatically generating high-quality solutions to optimization and search problems. This automatic aspect of the algorithms and the mimicking of natural selection and genetics makes genetic programming an intelligent component of problem solving that is highly regarded for its efficiency and vast capabilities. With the ability to be modified and adapted, easily distributed, and effective in large-scale/wide variety of problems, genetic algorithms and programming can be utilized in many diverse industries. This multi-industry uses vary from finance and economics to business and management all the way to healthcare and the sciences. The use of genetic programming and algorithms goes beyond human capabilities, enhancing the business and processes of various essential industries and improving functionality along the way. The Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms covers the implementation, tools and technologies, and impact on society that genetic programming and algorithms have had throughout multiple industries. By taking a multi-industry approach, this book covers the fundamentals of genetic programming through its technological benefits and challenges along with the latest advancements and future outlooks for computer science. This book is ideal for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.
This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers from academia and industry up to date on the most recent developments in this field.
Book Synopsis Computational Methods for Molecular Imaging by : Fei Gao
Download or read book Computational Methods for Molecular Imaging written by Fei Gao and published by Springer. This book was released on 2015-06-11 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to: • Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities • Molecular Imaging Enhancement • Data Analysis of Clinical & Pre-clinical Molecular Imaging • Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.) • Machine Learning and Data Mining in Molecular Imaging. Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization. This work will bring readers from academia and industry up to date on the most recent developments in this field.
