Advanced Data Mining Techniques

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Advanced Data Mining Techniques

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Author by : David L. Olson, Dursun Delen
Languange Used : English, France, Spanish, Italia and chinese
Page : 180
Isbn : 9783540769170
Identifier : 354076917X
Release : 2008-01-01
Publisher by : Springer Science & Business Media
Category : Business & Economics
Total Download : 8501945
Total Read : 982268
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Description : Read Now Advanced Data Mining Techniques by David L. Olson, Dursun Delen and you can download with pub, pdf, txt, doc, and more file format with free account. this book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. the book is organized in three parts. part i introduces concepts. part ii describes and demonstrates basic data mining algorithms. it also contains chapters on a number of different techniques often used in data mining. part iii focuses on business applications of data mining.

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence

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Author by : Trivedi, Shrawan Kumar, Dey, Shubhamoy, Kumar, Anil, Panda, Tapan Kumar
Languange Used : English, France, Spanish, Italia and chinese
Page : 438
Isbn : 1522520325
Identifier : 9781522520320
Release : 2017-02-14
Publisher by : IGI Global
Category : Computers
Total Download : 5282159
Total Read : 9281431
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Description : Read Now Handbook Of Research On Advanced Data Mining Techniques And Applications For Business Intelligence by Trivedi, Shrawan Kumar, Dey, Shubhamoy, Kumar, Anil, Panda, Tapan Kumar and you can download with pub, pdf, txt, doc, and more file format with free account. 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.

Data Mining Techniques For Marketing, Sales, and Customer Relationship Management

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Author by : Gordon S. Linoff, Michael J. A. Berry
Languange Used : English, France, Spanish, Italia and chinese
Page : 888
Isbn : 9781118087459
Identifier : 1118087453
Release : 2011-03-23
Publisher by : John Wiley & Sons
Category : Computers
Total Download : 7351310
Total Read : 2997279
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Description : Read Now Data Mining Techniques by Gordon S. Linoff, Michael J. A. Berry and you can download with pub, pdf, txt, doc, and more file format with free account. the leading introductory book on data mining, fully updated andrevised! when berry and linoff wrote the first edition of data miningtechniques in the late 1990s, data mining was just starting tomove out of the lab and into the office and has since grown tobecome an indispensable tool of modern business. this newedition—more than 50% new and revised— is asignificant update from the previous one, and shows you how toharness the newest data mining methods and techniques to solvecommon business problems. the duo of unparalleled authors shareinvaluable advice for improving response rates to direct marketingcampaigns, identifying new customer segments, and estimating creditrisk. in addition, they cover more advanced topics such aspreparing data for analysis and creating the necessaryinfrastructure for data mining at your company. features significant updates since the previous edition andupdates you on best practices for using data mining methods andtechniques for solving common business problems covers a new data mining technique in every chapter along withclear, concise explanations on how to apply each techniqueimmediately touches on core data mining techniques, including decisiontrees, neural networks, collaborative filtering, association rules,link analysis, survival analysis, and more provides best practices for performing data mining using simpletools such as excel data mining techniques, third edition covers a new datamining technique with each successive chapter and then demonstrateshow you can apply that technique for improved marketing, sales, andcustomer support to get immediate results.

Data Mining: Concepts and Techniques

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Author by : Jiawei Han, Jian Pei, Micheline Kamber
Languange Used : English, France, Spanish, Italia and chinese
Page : 744
Isbn : 9780123814807
Identifier : 0123814804
Release : 2011-06-09
Publisher by : Elsevier
Category : Computers
Total Download : 6700113
Total Read : 6903317
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Description : Read Now Data Mining Concepts And Techniques by Jiawei Han, Jian Pei, Micheline Kamber and you can download with pub, pdf, txt, doc, and more file format with free account. 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

Advanced Data Mining Technologies in Bioinformatics

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Author by : Hsu, Hui-Huang
Languange Used : English, France, Spanish, Italia and chinese
Page : 342
Isbn : 1591408652
Identifier : 9781591408659
Release : 2006-03-31
Publisher by : IGI Global
Category : Computers
Total Download : 3013909
Total Read : 3850961
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Description : Read Now Advanced Data Mining Technologies In Bioinformatics by Hsu, Hui-Huang and you can download with pub, pdf, txt, doc, and more file format with free account. "this book covers research topics of data mining on bioinformatics presenting the basics and problems of bioinformatics and applications of data mining technologies pertaining to the field"--provided by publisher.

Advanced Data Mining and Applications 7th International Conference, ADMA 2011, Beijing, China, December 17-19, 2011, Proceedings

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Author by : Jie Tang, Irwin King, Ling Chen, Jianyong Wang
Languange Used : English, France, Spanish, Italia and chinese
Page : 426
Isbn : 3642258522
Identifier : 9783642258527
Release : 2011-12-02
Publisher by : Springer Science & Business Media
Category : Computers
Total Download : 1092893
Total Read : 6909637
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Description : Read Now Advanced Data Mining And Applications by Jie Tang, Irwin King, Ling Chen, Jianyong Wang and you can download with pub, pdf, txt, doc, and more file format with free account. the two-volume set lnai 7120 and lnai 7121 constitutes the refereed proceedings of the 7th international conference on advanced data mining and applications, adma 2011, held in beijing, china, in december 2011. the 35 revised full papers and 29 short papers presented together with 3 keynote speeches were carefully reviewed and selected from 191 submissions. the papers cover a wide range of topics presenting original research findings in data mining, spanning applications, algorithms, software and systems, and applied disciplines.

Data Mining and Analysis Fundamental Concepts and Algorithms

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Author by : Mohammed J. Zaki, Wagner Meira, Jr
Languange Used : English, France, Spanish, Italia and chinese
Page : 562
Isbn : 0521766338
Identifier : 9780521766333
Release : 2014-05-12
Publisher by : Cambridge University Press
Category : Computers
Total Download : 8821000
Total Read : 1817036
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Description : Read Now Data Mining And Analysis by Mohammed J. Zaki, Wagner Meira, Jr and you can download with pub, pdf, txt, doc, and more file format with free account. a comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.

R Data Mining Implement data mining techniques through practical use cases and real world datasets

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Author by : Andrea Cirillo
Languange Used : English, France, Spanish, Italia and chinese
Page : 442
Isbn : 1787129233
Identifier : 9781787129238
Release : 2017-11-29
Publisher by : Packt Publishing Ltd
Category : Computers
Total Download : 1448374
Total Read : 8360668
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Description : Read Now R Data Mining by Andrea Cirillo and you can download with pub, pdf, txt, doc, and more file format with free account. mine valuable insights from your data using popular tools and techniques in r about this book understand the basics of data mining and why r is a perfect tool for it. manipulate your data using popular r packages such as ggplot2, dplyr, and so on to gather valuable business insights from it. apply effective data mining models to perform regression and classification tasks. who this book is for if you are a budding data scientist, or a data analyst with a basic knowledge of r, and want to get into the intricacies of data mining in a practical manner, this is the book for you. no previous experience of data mining is required. what you will learn master relevant packages such as dplyr, ggplot2 and so on for data mining learn how to effectively organize a data mining project through the crisp-dm methodology implement data cleaning and validation tasks to get your data ready for data mining activities execute exploratory data analysis both the numerical and the graphical way develop simple and multiple regression models along with logistic regression apply basic ensemble learning techniques to join together results from different data mining models perform text mining analysis from unstructured pdf files and textual data produce reports to effectively communicate objectives, methods, and insights of your analyses in detail r is widely used to leverage data mining techniques across many different industries, including finance, medicine, scientific research, and more. this book will empower you to produce and present impressive analyses from data, by selecting and implementing the appropriate data mining techniques in r. it will let you gain these powerful skills while immersing in a one of a kind data mining crime case, where you will be requested to help resolving a real fraud case affecting a commercial company, by the mean of both basic and advanced data mining techniques. while moving along the plot of the story you will effectively learn and practice on real data the various r packages commonly employed for this kind of tasks. you will also get the chance of apply some of the most popular and effective data mining models and algos, from the basic multiple linear regression to the most advanced support vector machines. unlike other data mining learning instruments, this book will effectively expose you the theory behind these models, their relevant assumptions and when they can be applied to the data you are facing. by the end of the book you will hold a new and powerful toolbox of instruments, exactly knowing when and how to employ each of them to solve your data mining problems and get the most out of your data. finally, to let you maximize the exposure to the concepts described and the learning process, the book comes packed with a reproducible bundle of commented r scripts and a practical set of data mining models cheat sheets. style and approach this book takes a practical, step-by-step approach to explain the concepts of data mining. practical use-cases involving real-world datasets are used throughout the book to clearly explain theoretical concepts.

Data Mining The Textbook

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Author by : Charu C. Aggarwal
Languange Used : English, France, Spanish, Italia and chinese
Page : 734
Isbn : 3319141422
Identifier : 9783319141428
Release : 2015-04-13
Publisher by : Springer
Category : Computers
Total Download : 3823651
Total Read : 8806550
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Description : Read Now Data Mining by Charu C. Aggarwal and you can download with pub, pdf, txt, doc, and more file format with free account. this textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues. it goes beyond the traditional focus on data mining problems to introduce advanced data types such as text, time series, discrete sequences, spatial data, graph data, and social networks. until now, no single book has addressed all these topics in a comprehensive and integrated way. the chapters of this book fall into one of three categories: fundamental chapters: data mining has four main problems, which correspond to clustering, classification, association pattern mining, and outlier analysis. these chapters comprehensively discuss a wide variety of methods for these problems. domain chapters: these chapters discuss the specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. application chapters: these chapters study important applications such as stream mining, web mining, ranking, recommendations, social networks, and privacy preservation. the domain chapters also have an applied flavor. appropriate for both introductory and advanced data mining courses, data mining: the textbook balances mathematical details and intuition. it contains the necessary mathematical details for professors and researchers, but it is presented in a simple and intuitive style to improve accessibility for students and industrial practitioners (including those with a limited mathematical background). numerous illustrations, examples, and exercises are included, with an emphasis on semantically interpretable examples. praise for data mining: the textbook - “as i read through this book, i have already decided to use it in my classes. this is a book written by an outstanding researcher who has made fundamental contributions to data mining, in a way that is both accessible and up to date. the book is complete with theory and practical use cases. it’s a must-have for students and professors alike!" -- qiang yang, chair of computer science and engineering at hong kong university of science and technology "this is the most amazing and comprehensive text book on data mining. it covers not only the fundamental problems, such as clustering, classification, outliers and frequent patterns, and different data types, including text, time series, sequences, spatial data and graphs, but also various applications, such as recommenders, web, social network and privacy. it is a great book for graduate students and researchers as well as practitioners." -- philip s. yu, uic distinguished professor and wexler chair in information technology at university of illinois at chicago

Statistical and Machine-Learning Data Mining Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition

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Author by : Bruce Ratner
Languange Used : English, France, Spanish, Italia and chinese
Page : 542
Isbn : 1466551216
Identifier : 9781466551213
Release : 2012-02-28
Publisher by : CRC Press
Category : Business & Economics
Total Download : 343497
Total Read : 5178568
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Description : Read Now Statistical And Machine Learning Data Mining by Bruce Ratner and you can download with pub, pdf, txt, doc, and more file format with free account. the second edition of a bestseller, statistical and machine-learning data mining: techniques for better predictive modeling and analysis of big data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. the first edition, titled statistical modeling and analysis for database marketing: effective techniques for mining big data, contained 17 chapters of innovative and practical statistical data mining techniques. in this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has completely revised, reorganized, and repositioned the original chapters and produced 14 new chapters of creative and useful machine-learning data mining techniques. in sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. the statistical data mining methods effectively consider big data for identifying structures (variables) with the appropriate predictive power in order to yield reliable and robust large-scale statistical models and analyses. in contrast, the author's own geniq model provides machine-learning solutions to common and virtually unapproachable statistical problems. geniq makes this possible — its utilitarian data mining features start where statistical data mining stops. this book contains essays offering detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. they address each methodology and assign its application to a specific type of problem. to better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. while this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.

Advanced Techniques in Knowledge Discovery and Data Mining

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Author by : Nikhil Pal
Languange Used : English, France, Spanish, Italia and chinese
Page : 256
Isbn : 9781846281839
Identifier : 1846281830
Release : 2007-12-31
Publisher by : Springer Science & Business Media
Category : Computers
Total Download : 7812436
Total Read : 2412714
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Description : Read Now Advanced Techniques In Knowledge Discovery And Data Mining by Nikhil Pal and you can download with pub, pdf, txt, doc, and more file format with free account. clear and concise explanations to understand the learning paradigms. chapters written by leading world experts.

Advanced Data Mining and Applications 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings

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Author by : Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li, Aixin Sun
Languange Used : English, France, Spanish, Italia and chinese
Page : 881
Isbn : 3319691791
Identifier : 9783319691794
Release : 2017-11-19
Publisher by : Springer
Category : Computers
Total Download : 5559776
Total Read : 2742136
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Description : Read Now Advanced Data Mining And Applications by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li, Aixin Sun and you can download with pub, pdf, txt, doc, and more file format with free account. this book constitutes the refereed proceedings of the 13th international conference on advanced data mining and applications, adma 2017, held in singapore in november 2017. the 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. the papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos.

Data Mining Techniques in CRM Inside Customer Segmentation

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Author by : Konstantinos K. Tsiptsis, Antonios Chorianopoulos
Languange Used : English, France, Spanish, Italia and chinese
Page : 372
Isbn : 1119965454
Identifier : 9781119965459
Release : 2011-08-24
Publisher by : John Wiley & Sons
Category : Computers
Total Download : 2190621
Total Read : 1716711
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Description : Read Now Data Mining Techniques In Crm by Konstantinos K. Tsiptsis, Antonios Chorianopoulos and you can download with pub, pdf, txt, doc, and more file format with free account. this is an applied handbook for the application of data mining techniques in the crm framework. it combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. it focuses on customer segmentation and presents guidelines for the development of actionable segmentation schemes. by using non-technical language it guides readers through all the phases of the data mining process.

Biological Data Mining

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Author by : Jake Y. Chen, Stefano Lonardi
Languange Used : English, France, Spanish, Italia and chinese
Page : 733
Isbn : 9781420086850
Identifier : 1420086855
Release : 2009-09-01
Publisher by : CRC Press
Category : Computers
Total Download : 3736134
Total Read : 1109273
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Description : Read Now Biological Data Mining by Jake Y. Chen, Stefano Lonardi and you can download with pub, pdf, txt, doc, and more file format with free account. like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. reflecting this growth, biological data mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics. the first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. the second section addresses emerging computational challenges in interpreting high-throughput omics data. the book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. the last part explores emerging data mining opportunities for biomedical applications. this volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. by studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

Data Mining: Techniques And Trends

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Author by : Gopalan & Sivaselvan
Languange Used : English, France, Spanish, Italia and chinese
Page : 129
Isbn : 812033812X
Identifier : 9788120338128
Release : 2009
Publisher by : PHI Learning Pvt. Ltd.
Category : Data mining
Total Download : 6731647
Total Read : 6153606
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Advanced Data Mining and Applications First International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Proceedings

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Author by : Xue Li, Shuliang Wang
Languange Used : English, France, Spanish, Italia and chinese
Page : 835
Isbn : 354027894X
Identifier : 9783540278948
Release : 2005-07-12
Publisher by : Springer Science & Business Media
Category : Computers
Total Download : 5002550
Total Read : 2073216
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Description : Read Now Advanced Data Mining And Applications by Xue Li, Shuliang Wang and you can download with pub, pdf, txt, doc, and more file format with free account. with the ever-growing power to generate, transmit and collect huge amounts of data, information overload is now an imminent problem to mankind. the overwhelming demand for information processing is not just about a better - derstanding of data, but also a better usage of data in a timely fashion. data mining, or knowledge discovery from databases, is proposed to gain insight into aspects of dataand to help peoplemakeinformed, sensible, andbetter decisions. at present, growing attention has been paid to the study, development and - plication of data mining. as a result there is an urgent need for sophisticated techniques and tools that can handle new ?elds of data mining, e.g., spatialdata mining, biomedical data mining, and mining on high-speed and time-variant data streams. the knowledge of data mining should also be expanded to new applications. the1stinternationalconferenceonadvanceddataminingandapplications (adma 2005) aimed to bring together the experts on data mining throughout the world. it provided a leading international forum for the dissemination of original research results in advanced data mining techniques, applications, al- rithms, software and systems, and di?erent applied disciplines. the conference attracted 539 online submissions and 63 mailing submissions from 25 di?erent countriesandareas.allfullpaperswerepeer reviewedbyatleastthreemembers of the program committee composed of international experts in data mining ?elds. a total number of 100 papers were accepted for the conference. amongst them 25 papers were selected as regular papers and 75 papers were selected as short papers, yielding a combined acceptance rate of 17%.