Data Mining Southeast Asia Edition
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Data Mining Southeast Asia Edition
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Author : Jiawei Han
language : en
Publisher: Elsevier
Release Date : 2006-04-06
Data Mining Southeast Asia Edition written by Jiawei Han and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-06 with Computers categories.
Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data— including stream data, sequence data, graph structured data, social network data, and multi-relational data. - A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data - Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning - Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects - Complete classroom support for instructors at www.mkp.com/datamining2e companion site
Data Mining Southeast Asia Edition
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Author : Jiawei Han
language : en
Publisher: Morgan Kaufmann
Release Date : 2006-04
Data Mining Southeast Asia Edition written by Jiawei Han and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04 with categories.
Data Mining Concepts And Techniques
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Author : Jiawei Han
language : en
Publisher: Elsevier
Release Date : 2011-06-09
Data Mining Concepts And Techniques written by Jiawei Han and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-09 with Computers categories.
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Data Mining And Predictive Analytics
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Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-16
Data Mining And Predictive Analytics written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-16 with Computers categories.
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: 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, with exclusive password-protected instructor content Data Mining and Predictive Analytics will appeal to computer science and statistic students, as well as students in MBA programs, and chief executives.
Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence
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Author : Trivedi, Shrawan Kumar
language : en
Publisher: IGI Global
Release Date : 2017-02-14
Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence written by Trivedi, Shrawan Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-14 with Computers categories.
The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.
Improving Knowledge Discovery Through The Integration Of Data Mining Techniques
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Author : Usman, Muhammad
language : en
Publisher: IGI Global
Release Date : 2015-08-03
Improving Knowledge Discovery Through The Integration Of Data Mining Techniques written by Usman, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-08-03 with Computers categories.
Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other’s methods to facilitate knowledge discovery. Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.
Machine Learning And Data Mining In Pattern Recognition
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Author : Petra Perner
language : en
Publisher: Springer
Release Date : 2015-06-30
Machine Learning And Data Mining In Pattern Recognition written by Petra Perner and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-30 with Computers categories.
This book constitutes the refereed proceedings of the 11th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2015, held in Hamburg, Germany in July 2015. The 41 full papers presented were carefully reviewed and selected from 123 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.
Applied Machine Learning For Data Science Practitioners
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Author : Vidya Subramanian
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-01
Applied Machine Learning For Data Science Practitioners written by Vidya Subramanian and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-01 with Mathematics categories.
A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the foundation for understanding ML. Data Preparation covers the process of framing ML problems and preparing data and features for modeling. ML Problem Solving introduces you to a range of ML algorithms, including Regression, Classification, Ranking, Clustering, Patterns, Time Series, and Anomaly Detection. Model Optimization explores frameworks, decision trees, and ensemble methods to enhance performance and guide the selection of the most effective model. ML Ethics addresses ethical considerations, including fairness, accountability, transparency, and ethics. Model Deployment and Monitoring focuses on production deployment, performance monitoring, and adapting to model drift.
Data Mining
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Author : Sushmita Mitra
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-21
Data Mining written by Sushmita Mitra and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-21 with Computers categories.
First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining Discusses principles and classical algorithms on string matching and their role in data mining
Cyber Criminology
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Author : Hamid Jahankhani
language : en
Publisher: Springer
Release Date : 2018-11-27
Cyber Criminology written by Hamid Jahankhani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-27 with Social Science categories.
This book provides a comprehensive overview of the current and emerging challenges of cyber criminology, victimization and profiling. It is a compilation of the outcomes of the collaboration between researchers and practitioners in the cyber criminology field, IT law and security field. As Governments, corporations, security firms, and individuals look to tomorrow’s cyber security challenges, this book provides a reference point for experts and forward-thinking analysts at a time when the debate over how we plan for the cyber-security of the future has become a major concern. Many criminological perspectives define crime in terms of social, cultural and material characteristics, and view crimes as taking place at a specific geographic location. This definition has allowed crime to be characterised, and crime prevention, mapping and measurement methods to be tailored to specific target audiences. However, this characterisation cannot be carried over to cybercrime, because the environment in which such crime is committed cannot be pinpointed to a geographical location, or distinctive social or cultural groups. Due to the rapid changes in technology, cyber criminals’ behaviour has become dynamic, making it necessary to reclassify the typology being currently used. Essentially, cyber criminals’ behaviour is evolving over time as they learn from their actions and others’ experiences, and enhance their skills. The offender signature, which is a repetitive ritualistic behaviour that offenders often display at the crime scene, provides law enforcement agencies an appropriate profiling tool and offers investigators the opportunity to understand the motivations that perpetrate such crimes. This has helped researchers classify the type of perpetrator being sought. This book offers readers insights into the psychology of cyber criminals, and understanding and analysing their motives and the methodologies they adopt. With an understanding of these motives, researchers, governments and practitioners can take effective measures to tackle cybercrime and reduce victimization.