aftab yaseen s m zakariya and m q rafiq association rules mining for ais based classification

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Gordon Linoff S. Data Mining Techniques. For Marketing, Sales, and Customer Relationship Management

Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis

3889.55 рублей

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Jesse Pines M. Evidence-Based Emergency Care. Diagnostic Testing and Clinical Decision Rules

This book for emergency physicians and fellows training in emergency medicine provides evidence-based information on what diagnostic tests to ask for and when and how to use particular decision rules. The new edition builds on the success of the current book by modifying the presentation of the evidence, increasing the coverage, and updating the current information throughout.

7720.81 рублей

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Giudici Paolo Applied Data Mining for Business and Industry

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.

14391.35 рублей

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Mourad Elloumi Biological Knowledge Discovery Handbook. Preprocessing, Mining and Postprocessing of Biological Data

The first comprehensive overview of preprocessing, mining, and postprocessing of biological data Molecular biology is undergoing exponential growth in both the volume and complexity of biological data—and knowledge discovery offers the capacity to automate complex search and data analysis tasks. This book presents a vast overview of the most recent developments on techniques and approaches in the field of biological knowledge discovery and data mining (KDD)—providing in-depth fundamental and technical field information on the most important topics encountered. Written by top experts, Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data covers the three main phases of knowledge discovery (data preprocessing, data processing—also known as data mining—and data postprocessing) and analyzes both verification systems and discovery systems. BIOLOGICAL DATA PREPROCESSING Part A: Biological Data Management Part B: Biological Data Modeling Part C: Biological Feature Extraction Part D Biological Feature Selection BIOLOGICAL DATA MINING Part E: Regression Analysis of Biological Data Part F Biological Data Clustering Part G: Biological Data Classification Part H: Association Rules Learning from Biological Data Part I: Text Mining and Application to Biological Data Part J: High-Performance Computing for Biological Data Mining Combining sound theory with practical applications in molecular biology, Biological Knowledge Discovery Handbook is ideal for courses in bioinformatics and biological KDD as well as for practitioners and professional researchers in computer science, life science, and mathematics.

14022.96 рублей

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DongHun Kang Modeling and Simulation of Discrete Event Systems

Computer modeling and simulation (M&S) allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems. Based on over 20 years of evolution within a classroom environment, as well as on decades-long experience in developing simulation-based solutions for high-tech industries, Modeling and Simulation of Discrete-Event Systems is the only book on DES-M&S in which all the major DES modeling formalisms – activity-based, process-oriented, state-based, and event-based – are covered in a unified manner: A well-defined procedure for building a formal model in the form of event graph, ACD, or state graph Diverse types of modeling templates and examples that can be used as building blocks for a complex, real-life model A systematic, easy-to-follow procedure combined with sample C# codes for developing simulators in various modeling formalisms Simple tutorials as well as sample model files for using popular off-the-shelf simulators such as SIGMA®, ACE®, and Arena® Up-to-date research results as well as research issues and directions in DES-M&S Modeling and Simulation of Discrete-Event Systems is an ideal textbook for undergraduate and graduate students of simulation/industrial engineering and computer science, as well as for simulation practitioners and researchers.

9224.13 рублей

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Daniel Larose T. Data Mining and Predictive Analytics

Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis. The authors apply a unified “white box” approach to data mining methods and models. This approach is designed to walk readers through the operations and nuances of the various methods, using small data sets, so readers can gain an insight into the inner workings of the method under review. Chapters provide readers with hands-on analysis problems, representing an opportunity for readers to apply their newly-acquired data mining expertise to solving real problems using large, real-world data sets. Data Mining and Predictive Analytics, Second Edition: Offers comprehensive coverage of association rules, clustering, neural networks, logistic regression, multivariate analysis, and R statistical programming language Features over 750 chapter exercises, allowing readers to assess their understanding of the new material Provides a detailed case study that brings together the lessons learned in the book Includes access to the companion website, www.dataminingconsultant.com, with exclusive password-protected instructor content Data Mining and Predictive Analytics, Second Edition will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.

10498.36 рублей

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Victor Rudenno The Mining Valuation Handbook. Mining and Energy Valuation for Investors and Management

The essential guide to investing in mining opportunities, now in its Fourth Edition A comprehensive guide to mining investment analysis designed for use by financial and mining analysts, executives, and investors, The Mining Valuation Handbook: Mining and Energy Valuation for Investors and Management has become an essential resource for assessing the value and investment potential of mining opportunities. Fully revised and updated, this fourth edition of the classic text provides new and up-to-date information to better explain the mysteries surrounding the resources industry. Written by Victor Rudenno, a leading global expert on mining investment analysis and consultant to mining companies, financial bodies, and governments, The Mining Valuation Handbook: Mining and Energy Valuation for Investors and Management, Fourth Edition covers a wide range of essential topics, including: feasibility studies, commodity values and forecasting, classification of resources and reserves, indicative capital and operating costs, valuation and pricing techniques, qualifying risk, the impact of exploration and expansion, and more. Fourth edition of the bestselling text on assessing mining investment opportunities Author Victor Rudenno is a respected global expert on mining investment analysis Key topics, including feasibility studies, valuation techniques, and risk qualification are covered in detail Packed with invaluable mining information for the financial industry and financial information for the mining industry, The Mining Valuation Handbook is the definitive guide to assessing and investing in mining opportunities.

10890.75 рублей

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Stéphane Tufféry Data Mining and Statistics for Decision Making

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

8008.59 рублей

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Pawel Cichosz Data Mining Algorithms. Explained Using R

Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for building classification, regression, and clustering models, as well as techniques used for attribute selection and transformation, model quality evaluation, and creating model ensembles. The author presents many of the important topics and methodologies widely used in data mining, whilst demonstrating the internal operation and usage of data mining algorithms using examples in R.

5999.06 рублей

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Gordon Linoff S. Data Mining Techniques. For Marketing, Sales, and Customer Relationship Management

The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous one, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more Provides best practices for performing data mining using simple tools such as Excel Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results.

3241.3 рублей

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Ying Tan Artificial Immune System. Applications in Computer Security

This book deals with malware detection in terms of Artificial Immune System (AIS), and presents a number of AIS models and immune-based feature extraction approaches as well as their applications in computer security Covers all of the current achievements in computer security based on immune principles, which were obtained by the Computational Intelligence Laboratory of Peking University, China Includes state-of-the-art information on designing and developing artificial immune systems (AIS) and AIS-based solutions to computer security issues Presents new concepts such as immune danger theory, immune concentration, and class-wise information gain (CIG)

7874.48 рублей

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Jerry Couretas M. An Introduction to Cyber Modeling and Simulation

Introduces readers to the field of cyber modeling and simulation and examines current developments in the US and internationally This book provides an overview of cyber modeling and simulation (M&S) developments. Using scenarios, courses of action (COAs), and current M&S and simulation environments, the author presents the overall information assurance process, incorporating the people, policies, processes, and technologies currently available in the field. The author ties up the various threads that currently compose cyber M&S into a coherent view of what is measurable, simulative, and usable in order to evaluate systems for assured operation. An Introduction to Cyber Modeling and Simulation provides the reader with examples of tools and technologies currently available for performing cyber modeling and simulation. It examines how decision-making processes may benefit from M&S in cyber defense. It also examines example emulators, simulators and their potential combination. The book also takes a look at corresponding verification and validation (V&V) processes, which provide the operational community with confidence in knowing that cyber models represent the real world. This book: Explores the role of cyber M&S in decision making Provides a method for contextualizing and understanding cyber risk Shows how concepts such the Risk Management Framework (RMF) leverage multiple processes and policies into a coherent whole Evaluates standards for pure IT operations, «cyber for cyber,» and operational/mission cyber evaluations—"cyber for others" Develops a method for estimating both the vulnerability of the system (i.e., time to exploit) and provides an approach for mitigating risk via policy, training, and technology alternatives Uses a model-based approach An Introduction to Cyber Modeling and Simulation is a must read for all technical professionals and students wishing to expand their knowledge of cyber M&S for future professional work.

8103.24 рублей

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Albalate Amparo Semi-Supervised and Unsupervised Machine Learning. Novel Strategies

This book provides a detailed and up-to-date overview on classification and data mining methods. The first part is focused on supervised classification algorithms and their applications, including recent research on the combination of classifiers. The second part deals with unsupervised data mining and knowledge discovery, with special attention to text mining. Discovering the underlying structure on a data set has been a key research topic associated to unsupervised techniques with multiple applications and challenges, from web-content mining to the inference of cancer subtypes in genomic microarray data. Among those, the book focuses on a new application for dialog systems which can be thereby made adaptable and portable to different domains. Clustering evaluation metrics and new approaches, such as the ensembles of clustering algorithms, are also described.

8790.39 рублей

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RULES & REGULATIONS FOR THE CONSTRUCTION AND CLASSIFICATION OF STEEL VESSELS 1862 - 1969

Издание на английском языке. New York. 1969. American Bureau of Shipping., 1969. Yearly edition. (2), XXX, (2), 537 PP (one of them folded) with numerous figures and tables including 7 tables "Scantlings / Equipments" . Cloth cover, gilt device on front board, gilt title "Rules for Building and Classing Steel Vessels 1969" on front board and spine.

136 рублей

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Ekins Sean Pharmaceutical Data Mining. Approaches and Applications for Drug Discovery

Leading experts illustrate how sophisticated computational data mining techniques can impact contemporary drug discovery and development In the era of post-genomic drug development, extracting and applying knowledge from chemical, biological, and clinical data is one of the greatest challenges facing the pharmaceutical industry. Pharmaceutical Data Mining brings together contributions from leading academic and industrial scientists, who address both the implementation of new data mining technologies and application issues in the industry. This accessible, comprehensive collection discusses important theoretical and practical aspects of pharmaceutical data mining, focusing on diverse approaches for drug discovery—including chemogenomics, toxicogenomics, and individual drug response prediction. The five main sections of this volume cover: A general overview of the discipline, from its foundations to contemporary industrial applications Chemoinformatics-based applications Bioinformatics-based applications Data mining methods in clinical development Data mining algorithms, technologies, and software tools, with emphasis on advanced algorithms and software that are currently used in the industry or represent promising approaches In one concentrated reference, Pharmaceutical Data Mining reveals the role and possibilities of these sophisticated techniques in contemporary drug discovery and development. It is ideal for graduate-level courses covering pharmaceutical science, computational chemistry, and bioinformatics. In addition, it provides insight to pharmaceutical scientists, principal investigators, principal scientists, research directors, and all scientists working in the field of drug discovery and development and associated industries.

12446.57 рублей

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Перчатки Reebok S/M серый RAEL-11133GR

Вид: перчатки Размер: S/M Пол: унисекс Цвет: черный/серый Страна-производитель: Китай

1690 рублей

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Introduces readers to the field of cyber modeling and simulation and examines current developments in the US and internationally This book provides an overview of cyber modeling and simulation (M&S) developments. Using scenarios, courses of action (COAs), and current M&S and simulation environments, the author presents the overall information assurance process, incorporating the people, policies, processes, and technologies currently available in the field. The author ties up the various threads that currently compose cyber M&S into a coherent view of what is measurable, simulative, and usable in order to evaluate systems for assured operation. An Introduction to Cyber Modeling and Simulation provides the reader with examples of tools and technologies currently available for performing cyber modeling and simulation. It examines how decision-making processes may benefit from M&S in cyber defense. It also examines example emulators, simulators and their potential combination. The book also takes a look at corresponding verification and validation (V&V) processes, which provide the operational community with confidence in knowing that cyber models represent the real world. This book: Explores the role of cyber M&S in decision making Provides a method for contextualizing and understanding cyber risk Shows how concepts such the Risk Management Framework (RMF) leverage multiple processes and policies into a coherent whole Evaluates standards for pure IT operations, «cyber for cyber,» and operational/mission cyber evaluations—"cyber for others" Develops a method for estimating both the vulnerability of the system (i.e., time to exploit) and provides an approach for mitigating risk via policy, training, and technology alternatives Uses a model-based approach An Introduction to Cyber Modeling and Simulation is a must read for all technical professionals and students wishing to expand their knowledge of cyber M&S for future professional work.

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