Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications, Raza Muhammad Summair, Qamar Usman
Автор: Raza Muhammad Summair, Qamar Usman Название: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications ISBN: 9813291656 ISBN-13(EAN): 9789813291652 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a comprehensive introduction to rough set-based feature selection. Rough set theory, first proposed by Zdzislaw Pawlak in 1982, continues to evolve. Concerned with the classification and analysis of imprecise or uncertain information and knowledge, it has become a prominent tool for data analysis, and enables the reader to systematically study all topics in rough set theory (RST) including preliminaries, advanced concepts, and feature selection using RST. The book is supplemented with an RST-based API library that can be used to implement several RST concepts and RST-based feature selection algorithms.The book provides an essential reference guide for students, researchers, and developers working in the areas of feature selection, knowledge discovery, and reasoning with uncertainty, especially those who are working in RST and granular computing. The primary audience of this book is the research community using rough set theory (RST) to perform feature selection (FS) on large-scale datasets in various domains. However, any community interested in feature selection such as medical, banking, and finance can also benefit from the book. This second edition also covers the dominance-based rough set approach and fuzzy rough sets. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle. In turn, fuzzy rough sets are fuzzy generalizations of rough sets. An API library for the DRSA is also provided with the second edition of the book.
Автор: Raza Muhammad Summair, Qamar Usman Название: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications ISBN: 9813291680 ISBN-13(EAN): 9789813291683 Издательство: Springer Рейтинг: Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides a comprehensive introduction to rough set-based feature selection. The dominance-based rough set approach (DRSA) is an extension of the conventional rough set approach and supports the preference order using the dominance principle.
Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner ISBN: 1118729277 ISBN-13(EAN): 9781118729274 Издательство: Wiley Рейтинг: Цена: 118270.00 T Наличие на складе: Поставка под заказ. Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.
Автор: Zhao Haitao, Lai Zhihui, Leung Henry Название: Feature Learning and Understanding: Algorithms and Applications ISBN: 3030407934 ISBN-13(EAN): 9783030407933 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Chapter1. A Gentle Introduction to Feature Learning.- Chapter2. Latent Semantic Feature Learning.- Chapter3. Principal Component Analysis.- Chapter4. Local-Geometrical-Structure-based Feature Learning.- Chapter5. Linear Discriminant Analysis.- Chapter6. Kernel-based nonlinear feature learning.- Chapter7. Sparse feature learning.- Chapter8. Low rank feature learning.- Chapter9. Tensor-based Feature Learning.- Chapter10. Neural-network-based Feature Learning: Autoencoder.- Chapter11. Neural-network-based Feature Learning: Convolutional Neural Network.- Chapter12. Neural-network-based Feature Learning: Recurrent Neural Network.
Автор: Qamar Usman, Raza Muhammad Summair Название: Data Science Concepts and Techniques with Applications ISBN: 981156132X ISBN-13(EAN): 9789811561320 Издательство: Springer Цена: 46570.00 T Наличие на складе: Поставка под заказ. Описание: This book comprehensively covers the topic of data science. Followed by discussion on wide range of applications of data science and widely used techniques in data science.The second section is devoted to the tools and techniques of data science.
Автор: Chaki Jyotismita, Dey Nilanjan Название: Image Color Feature Extraction Techniques: Fundamentals and Applications ISBN: 9811557608 ISBN-13(EAN): 9789811557606 Издательство: Springer Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces a range of image color feature extraction techniques. In addition, the book can be used as an introduction to image color feature techniques for those who are new to the research field and software.
Автор: Kar Krishnendu Название: Mastering Computer Vision with TensorFlow 2.x: Build advanced computer vision applications using machine learning and deep learning techniques ISBN: 1838827064 ISBN-13(EAN): 9781838827069 Издательство: Неизвестно Рейтинг: Цена: 60070.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.
Delve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python
Key Features
Understand how to obtain financial data via Quandl or internal systems
Automate commercial banking using artificial intelligence and Python programs
Implement various artificial intelligence models to make personal banking easy
Book Description
Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI.
You'll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you'll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you'll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you'll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you'll get to grips with some real-world AI considerations in the field of banking.
By the end of this book, you'll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI.
What you will learn
Automate commercial bank pricing with reinforcement learning
Perform technical analysis using convolutional layers in Keras
Use natural language processing (NLP) for predicting market responses and visualizing them using graph databases
Deploy a robot advisor to manage your personal finances via Open Bank API
Sense market needs using sentiment analysis for algorithmic marketing
Explore AI adoption in banking using practical examples
Understand how to obtain financial data from commercial, open, and internal sources
Who this book is for
This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.
Knowledge Capital that ensures sustainability, competitiveness and stability of an organization can be regenerated in value-added form and made available for the creation of quality products and services by application of Knowledge Management System (KMS), across a diverse range of fields. Knowledge Management Systems: Concepts, Technologies and Practices focuses upon the standard procedures and technologies underlying the development of a KMS, while discussing some novel concepts like Virtuous KM Cycle, MASK techniques, Daisy Model and AI-KM Model.
Автор: Lech Polkowski; Shusaku Tsumoto; Tsau Y. Lin Название: Rough Set Methods and Applications ISBN: 3662003767 ISBN-13(EAN): 9783662003763 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Akama Seiki, Kudo Yasuo, Murai Tetsuya Название: Topics in Rough Set Theory: Current Applications to Granular Computing ISBN: 3030295680 ISBN-13(EAN): 9783030295684 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book discusses current topics in rough set theory. Since Pawlak`s rough set theory was first proposed to offer a basis for imprecise and uncertain data and reasoning from data, many workers have investigated its foundations and applications.
Автор: Bingi Kishore, Ibrahim Rosdiazli, Karsiti Mohd Noh Название: Fractional-Order Systems and Pid Controllers: Using Scilab and Curve Fitting Based Approximation Techniques ISBN: 303033936X ISBN-13(EAN): 9783030339364 Издательство: Springer Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents a detailed study on fractional-order, set-point, weighted PID control strategies and the development of curve-fitting-based approximation techniques for fractional-order parameters.
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