Advanced Studies In Classification And Data Science
DOWNLOAD
Download Advanced Studies In Classification And Data Science PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Advanced Studies In Classification And Data Science book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Advanced Studies In Classification And Data Science
DOWNLOAD
Author : Tadashi Imaizumi
language : en
Publisher: Springer Nature
Release Date : 2020-09-25
Advanced Studies In Classification And Data Science written by Tadashi Imaizumi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-25 with Mathematics categories.
This edited volume focuses on the latest developments in classification and data science and covers a wide range of topics in the context of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, data visualization, multivariate statistical methods, and various applications to real data in the social sciences, medical sciences, and other disciplines. In addition to sharing theoretical and methodological findings, the book shows how to apply the proposed methods to a variety of problems — e.g. in consumer behavior, decision-making, marketing data and social network structures. Both methodological aspects and applications to a wide range of areas such as economics, behavioral science, marketing science, management science and the social sciences are covered. The book is chiefly intended for researchers and practitioners who are interested in the latest developments and practical applications in these fields, as well as applied statisticians and data analysts. Its combination of methodological advances with a wide range of real-world applications gathered from several fields makes it of unique value in helping readers solve their research problems.
Advanced Studies In Behaviormetrics And Data Science
DOWNLOAD
Author : Tadashi Imaizumi
language : en
Publisher: Springer Nature
Release Date : 2020-04-17
Advanced Studies In Behaviormetrics And Data Science written by Tadashi Imaizumi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-17 with Social Science categories.
This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.
Classification Big Data Analysis And Statistical Learning
DOWNLOAD
Author : Francesco Mola
language : en
Publisher:
Release Date : 2018
Classification Big Data Analysis And Statistical Learning written by Francesco Mola and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Mathematical statistics categories.
This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8-10, 2015.
Advances In Computing And Data Sciences
DOWNLOAD
Author : Mayank Singh
language : en
Publisher: Springer Nature
Release Date : 2021-10-20
Advances In Computing And Data Sciences written by Mayank Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-20 with Computers categories.
This two-volume book constitutes the post-conference proceedings of the 5th International Conference on Advances in Computing and Data Sciences, ICACDS 2021, held in Nashik, India, in April 2021.* The 103 full papers were carefully reviewed and selected from 781 submissions. Part II is devoted to data sciences, organizing principles, medical technologies, computational linguistics etc. *The conference was held virtually due to the COVID-19 pandemic.
Advanced Data Analytics Using Python
DOWNLOAD
Author : Sayan Mukhopadhyay
language : en
Publisher: Apress
Release Date : 2018-03-29
Advanced Data Analytics Using Python written by Sayan Mukhopadhyay and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-29 with Computers categories.
Gain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis. After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects. What You Will Learn Work with data analysis techniques such as classification, clustering, regression, and forecasting Handle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQL Examine the different big data frameworks, including Hadoop and Spark Discover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLP Who This Book Is For Data scientists and software developers interested in the field of data analytics.
Research Advances In Intelligent Computing
DOWNLOAD
Author : Anshul Verma
language : en
Publisher: CRC Press
Release Date : 2023-03-23
Research Advances In Intelligent Computing written by Anshul Verma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-23 with Computers categories.
Since the invention of computers and other similar machines, scientists and researchers have been trying very hard to enhance their capabilities to perform various tasks. As a result, the capabilities of computers are growing exponentially day by day in terms of diverse working domains, versatile jobs, processing speed, and reduced size. Now, we are in the race to make these machines as intelligent as human beings. Artificial intelligence (AI) came up as a way of making a computer or computer software think in a similar manner to the way that humans think. AI is inspired by the study of human brain, including how humans think, learn, decide, and act while trying to solve a problem. The outcomes of this study are the basis of developing intelligent software and systems or intelligent computing (IC). An IC system has the capabilities of reasoning, learning, problem-solving, perception, and linguistic intelligence. IC systems consist of AI techniques as well as other emerging techniques that make a system intelligent. The use of IC has been seen in almost every sub-domain of computer science such as networking, software engineering, gaming, natural language processing, computer vision, image processing, data science, robotics, expert systems, and security. Nowadays, IC is also useful for solving various complex problems in diverse domains such as for predicting disease in medical science, predicting land fertility or crop productivity in agricultural science, predicting market growth in economics, and weather forecasting. For all these reasons, this book presents the advances in AI techniques, under the umbrella of IC. In this context, the book includes recent research that has been done in the areas of machine learning, neural networks, deep learning, evolutionary algorithms, genetic algorithms, swarm intelligence, fuzzy systems, and so on. This book discusses recent theoretical, algorithmic, simulation, and implementation-based advancements related to IC.
Advanced Classification Techniques For Healthcare Analysis
DOWNLOAD
Author : Chinmay Chakraborty
language : en
Publisher: IGI Global, Medical Information Science Reference
Release Date : 2018-11-16
Advanced Classification Techniques For Healthcare Analysis written by Chinmay Chakraborty and has been published by IGI Global, Medical Information Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-16 with Diagnostic imaging categories.
"This book focuses on classification techniques which broadly deals in delivery of quality, accurate and affordable healthcare. It also examines the potential for making faster advances in many scientific disciplines and improving the profitability and success of different enterprises"--
Modern Quantification Theory
DOWNLOAD
Author : Shizuhiko Nishisato
language : en
Publisher: Springer Nature
Release Date : 2021-07-22
Modern Quantification Theory written by Shizuhiko Nishisato and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-22 with Social Science categories.
This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis. These multiple identities are a consequence of its large number of properties that allow one to analyze and visualize the strength of variable association in an optimal solution. The book contains modern quantification theory for analyzing the association between two and more categorical variables in a variety of applicative frameworks. Visualization has attracted much attention over the past decades and given rise to controversial opinions. One may consider variations of plotting systems used in the construction of the classic correspondence plot, the biplot, the Carroll-Green-Schaffer scaling, or a new approach in doubled multidimensional space as presented in the book. There are even arguments for no visualization at all. The purpose of this book therefore is to shed new light on time-honored graphical procedures with critical reviews, new ideas, and future directions as alternatives. This stimulating volume is written with fresh new ideas from the traditional framework and the contemporary points of view. It thus offers readers a deep understanding of the ever-evolving nature of quantification theory and its practice. Part I starts with illustrating contingency table analysis with traditional joint graphical displays (symmetric, non-symmetric) and the CGS scaling and then explores logically correct graphs in doubled Euclidean space for both row and column variables. Part II covers a variety of mathematical approaches to the biplot strategy in graphing a data structure, providing a useful source for this modern approach to graphical display. Part II is also concerned with a number of alternative approaches to the joint graphical display such as bimodal cluster analysis and other statistical problems relevant to quantification theory.
Mathematical Problems In Data Science
DOWNLOAD
Author : Li M. Chen
language : en
Publisher: Springer
Release Date : 2015-12-15
Mathematical Problems In Data Science written by Li M. Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-15 with Computers categories.
This book describes current problems in data science and Big Data. Key topics are data classification, Graph Cut, the Laplacian Matrix, Google Page Rank, efficient algorithms, hardness of problems, different types of big data, geometric data structures, topological data processing, and various learning methods. For unsolved problems such as incomplete data relation and reconstruction, the book includes possible solutions and both statistical and computational methods for data analysis. Initial chapters focus on exploring the properties of incomplete data sets and partial-connectedness among data points or data sets. Discussions also cover the completion problem of Netflix matrix; machine learning method on massive data sets; image segmentation and video search. This book introduces software tools for data science and Big Data such MapReduce, Hadoop, and Spark. This book contains three parts. The first part explores the fundamental tools of data science. It includes basic graph theoretical methods, statistical and AI methods for massive data sets. In second part, chapters focus on the procedural treatment of data science problems including machine learning methods, mathematical image and video processing, topological data analysis, and statistical methods. The final section provides case studies on special topics in variational learning, manifold learning, business and financial data rec overy, geometric search, and computing models. Mathematical Problems in Data Science is a valuable resource for researchers and professionals working in data science, information systems and networks. Advanced-level students studying computer science, electrical engineering and mathematics will also find the content helpful.
Choosing Chinese Universities
DOWNLOAD
Author : Alice Y.C. Te
language : en
Publisher: Routledge
Release Date : 2022-10-07
Choosing Chinese Universities written by Alice Y.C. Te and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-07 with Education categories.
This book unpacks the complex dynamics of Hong Kong students’ choice in pursuing undergraduate education at the universities of Mainland China. Drawing on an empirical study based on interviews with 51 students, this book investigates how macro political/economic factors, institutional influences, parental influence, and students’ personal motivations have shaped students’ eventual choice of university. Building on Perna’s integrated model of college choice and Lee’s push-pull mobility model, this book conceptualizes that students’ border crossing from Hong Kong to Mainland China for higher education is a trans-contextualized negotiated choice under the "One Country, Two Systems" principle. The findings reveal that during the decision-making process, influencing factors have conditioned four archetypes of student choice: Pragmatists, Achievers, Averages, and Underachievers. The book closes by proposing an enhanced integrated model of college choice that encompasses both rational motives and sociological factors, and examines the theoretical significance and practical implications of the qualitative study. With its focus on student choice and experiences of studying in China, this book’s research and policy findings will interest researchers, university administrators, school principals, and teachers.