Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained.
Автор: Gonzalez Fabio a., Romero Eduardo Название: Biomedical Image Analysis and Machine Learning Technologies: Applications and Techniques ISBN: 1605669563 ISBN-13(EAN): 9781605669564 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 240320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides a panorama of the current boundary between biomedical complexity coming from the medical image context and the multiple techniques which have been used for solving many of these problems. It will serve as a leading industry reference.
New Approaches in Intelligent Image Analysis- Techniques, Methodologies and Applications.- New Approaches for Hierarchical Image Decomposition, based on IDP, SVD, PCA and KPCA.- Intelligent Digital Signal Processing and Feature Extraction Methods.- Multi-Dimensional Data Clustering and Visualization via Echo State Networks.- Unsupervised Clustering of Natural Images in Automatic Image Annotation Systems.- An Evolutionary Optimization Control System for Remote Sensing Image Processing.- Tissue Segmentation Methods using 2D Histogram Modification in a Sequence of MR Brain Images.- Multistage Approach for Simple Kidney Cysts Segmentation in CT Images.- Audio Visual Attention Models in Mobile Robots Navigation.- Local Adaptive Image Processing.- Learning Techniques for Intelligent Access Control.- Experimental Evaluation of Opportunity to Improve the Resolution of the Acoustic Maps.
Автор: Sigala Marianna, Rahimi Roya, Thelwall Mike Название: Big Data and Innovation in Tourism, Travel, and Hospitality: Managerial Approaches, Techniques, and Applications ISBN: 9811363412 ISBN-13(EAN): 9789811363412 Издательство: Springer Рейтинг: Цена: 74530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings together multi-disciplinary research and practical evidence about the role and exploitation of big data in driving and supporting innovation in tourism.
Deep learning (DL) is a method of machine learning, running over artificial neural networks, that uses multiple layers to extract high-level features from large amounts of raw data. DL methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of DL and its applications in the field of biomedical engineering.
DL has been rapidly developed in recent years, in terms of both methodological constructs and practical applications. DL provides computational models of multiple processing layers to learn and represent data with higher levels of abstraction. It is able to implicitly capture intricate structures of large-scale data and is ideally suited to many of the hardware architectures that are currently available.
The ever-expanding amount of data that can be gathered through biomedical and clinical information sensing devices necessitates the development of machine learning and artificial intelligence techniques such as DL and convolutional neural networks to process and evaluate the data. Some examples of biomedical and clinical sensing devices that use DL include computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic particle imaging, electroencephalography/magnetoencephalography (EE/MEG), optical microscopy and tomography, photoacoustic tomography, electron tomography, and atomic force microscopy. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications provides the most complete coverage of DL applications in biomedical engineering available, including detailed real-world applications in areas such as computational neuroscience, neuroimaging, data fusion, medical image processing, neurological disorder diagnosis for diseases such as Alzheimer's, attention deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), tumor prediction, and translational multimodal imaging analysis.
Presents a comprehensive handbook of the biomedical engineering applications of DL, including computational neuroscience, neuroimaging, time series data such as MRI, functional MRI, CT, EEG, MEG, and data fusion of biomedical imaging data from disparate sources, such as X-Ray/CT.
Helps readers understand key concepts in DL applications for biomedical engineering and health care, including manifold learning, classification, clustering, and regression in neuroimaging data analysis.
Provides readers with key DL development techniques such as creation of algorithms and application of DL through artificial neural networks and convolutional neural networks.
Includes coverage of key application areas of DL such as early diagnosis of specific diseases such as Alzheimer's, ADHD, and ASD, and tumor prediction through MRI and translational multimodality imaging and biomedical applications such as detection, diagnostic analysis, quantitative measurements, and image guidance of ultrasonography.
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Автор: Hemanth, D. Jude Название: Intelligent Data Analysis for Biomedical Applications ISBN: 0128155531 ISBN-13(EAN): 9780128155530 Издательство: Elsevier Science Рейтинг: Цена: 114530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases.
Provides the methods and tools necessary for intelligent data analysis and gives solutions to problems resulting from automated data collection
Contains an analysis of medical databases to provide diagnostic expert systems
Addresses the integration of intelligent data analysis techniques within biomedical information systems
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
One of the main objectives of planning and design is the reflection of the works to the space. Therefore, the starting point of this book is to reveal the research conducted by different professions in the field of spatial planning and design. For this purpose, original researches on direct application and land were included. Planning and design studies need co-operation between professions in order to fulfill this philosophy. These activities are effective means of fulfilling the philosophy of sustainability. Planning and design is a tool to tell the story of a community, and how it’s past, present and future work together for a sustainable tomorrow. The design process in which the most appropriate spatial compositions are revealed by shaping the areas in the direction of planning decisions, develops in the continuation of the planning process. This book is for landscape architects and other planning and design professions. Theoretical foundations, theories, methods, and applications will be essential parts of this reference book. In addition, this book addresses several very different subjects of study; landscape management, biodiversity, landscape restoration, landscape design, urban design, urban planning and architectural design related to theory, practice and the results will be covered.
Автор: Exarchos Themis P., Papadopoulos Athanasios, Fotiadis Dimitrios I. Название: Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications ISBN: 160566314X ISBN-13(EAN): 9781605663142 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 221540.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Includes methodologies that introduce biomedical imaging in decision support systems and their applications in clinical practice. This book offers an overview of the field of image-guided medical and biological decision support. It features cross-referencing of key terms and information pertinent to diagnostic imaging and biomedical applications.
Автор: Pavel Matousek; Michael Morris Название: Emerging Raman Applications and Techniques in Biomedical and Pharmaceutical Fields ISBN: 3642262430 ISBN-13(EAN): 9783642262432 Издательство: Springer Рейтинг: Цена: 174130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents the latest technological advances in Raman spectroscopy that are presently redrawing the landscape of many fields of biomedical and pharmaceutical R&D. Numerous examples are given to illustrate the application of the new methods.
Автор: Toshihiko Tominaga, Yoshiki Oshida Название: Nickel-Titanium Materials: Biomedical Applications ISBN: 3110666219 ISBN-13(EAN): 9783110666212 Издательство: Walter de Gruyter Рейтинг: Цена: 1078540.00 T Наличие на складе: Нет в наличии. Описание:
Nickel-Titanium alloys are smart materials exhibiting unique properties such as superelasticity and shape-memory effect. The material has been used as orthodontic wires in the dental field for over 20 years. This book is a comprehensive overview to the field of Ni-Ti Materials and the physical, chemical and mechanical properties of this versatile alloy. In addition, complications and challenges exhibited in applications are also discussed.
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