Introduction To Data Mining And Its Applications

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Introduction to Data Mining and Its Applications

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Author by : S. Sumathi, S.N. Sivanandam
Languange Used : English, France, Spanish, Italia and chinese
Page : 828
Isbn : 3540343504
Identifier : 9783540343509
Release : 2006-09-26
Publisher by : Springer Science & Business Media
Category : Computers
Total Download : 371487
Total Read : 334408
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Description : Read Now Introduction To Data Mining And Its Applications by S. Sumathi, S.N. Sivanandam and you can download with pub, pdf, txt, doc, and more file format with free account. this book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in data base systems and new data base applications and is also designed to give a broad, yet in-depth overview of the field of data mining. data mining is a multidisciplinary field, drawing work from areas including database technology, ai, machine learning, nn, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization. this book is intended for a wide audience of readers who are not necessarily experts in data warehousing and data mining, but are interested in receiving a general introduction to these areas and their many practical applications. since data mining technology has become a hot topic not only among academic students but also for decision makers, it provides valuable hidden business and scientific intelligence from a large amount of historical data. it is also written for technical managers and executives as well as for technologists interested in learning about data mining.

Data Mining Techniques and Applications An Introduction

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Author by : Hongbo Du
Languange Used : English, France, Spanish, Italia and chinese
Page : 315
Isbn : 9781844808915
Identifier : 1844808912
Release : 2010
Publisher by :
Category : Data mining
Total Download : 1107876
Total Read : 5970014
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Description : Read Now Data Mining Techniques And Applications by Hongbo Du and you can download with pub, pdf, txt, doc, and more file format with free account. this concise and approachable introduction to data mining selects a mixture of data mining techniques originating from statistics, machine learning and databases, and presents them in an algorithmic approach. aimed primarily at undergraduate readers, it presents not only the fundamental principles and concepts of the subject in an easy-to-understand way, but also hands on, practical instruction on data mining techniques, that readers can put into practice as they go along using the freely downloadable weka toolkit. author hongbo du shares his years of commercial, as well as research-based, experience in the field through extensive examples and real-world case studies, highlighting how data mining solutions provided by software tools are used in practical problem solving. covering not only traditional areas of data mining such as association, clustering and classification, this text also explains topics such as data warehousing, online-analytic processing, and text mining.

Introduction to Data Mining

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Author by : Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, Vipin Kumar
Languange Used : English, France, Spanish, Italia and chinese
Page : 864
Isbn : 9780133128901
Identifier : 0133128903
Release : 2013
Publisher by : Addison-Wesley
Category : Computers
Total Download : 8168143
Total Read : 842164
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Description : Read Now Introduction To Data Mining by Pang-Ning Tan, Michael Steinbach, Anuj Karpatne, Vipin Kumar and you can download with pub, pdf, txt, doc, and more file format with free account. introducing the fundamental concepts and algorithms of data mining introduction to data mining, 2nd edition , gives a comprehensive overview of the background and general themes of data mining and is designed to be useful to students, instructors, researchers, and professionals. presented in a clear and accessible way, the book outlines fundamental concepts and algorithms for each topic, thus providing the reader with the necessary background for the application of data mining to real problems. the text helps readers understand the nuances of the subject, and includes important sections on classification, association analysis, and cluster analysis. this edition improves on the first iteration of the book, published over a decade ago, by addressing the significant changes in the industry as a result of advanced technology and data growth.

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 : 4860071
Total Read : 2633567
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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

Practical Applications of Data Mining

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Author by : Sang C. Suh
Languange Used : English, France, Spanish, Italia and chinese
Page : 414
Isbn : 0763785873
Identifier : 9780763785871
Release : 2012
Publisher by : Jones & Bartlett Publishers
Category : Computers
Total Download : 9563504
Total Read : 9930397
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Description : Read Now Practical Applications Of Data Mining by Sang C. Suh and you can download with pub, pdf, txt, doc, and more file format with free account. various topics of data mining techniques are identified and described throughout, including clustering, association rules, rough set theory, probability theory, neural networks, classification, and fuzzy logic. each of these techniques is explored with a theoretical introduction and its effectiveness is demonstrated with various chapter examples.

Biological Data Mining and Its Applications in Healthcare

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Author by : Xiaoli Li, See-Kiong Ng, Jason T L Wang
Languange Used : English, France, Spanish, Italia and chinese
Page : 436
Isbn : 9814551023
Identifier : 9789814551021
Release : 2013-11-28
Publisher by : World Scientific
Category : Computers
Total Download : 4346233
Total Read : 1040303
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Description : Read Now Biological Data Mining And Its Applications In Healthcare by Xiaoli Li, See-Kiong Ng, Jason T L Wang and you can download with pub, pdf, txt, doc, and more file format with free account. biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. this has resulted in a flood of biological and clinical data from genomic and protein sequences, dna microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. to exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. this book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains. contents:sequence analysis:mining the sequence databases for homology detection: application to recognition of functions of trypanosoma brucei brucei proteins and drug targets (g ramakrishnan, v s gowri, r mudgal, n r chandra and n srinivasan)identification of genes and their regulatory regions based on multiple physical and structural properties of a dna sequence (xi yang, nancy yu song and hong yan)mining genomic sequence data for related sequences using pairwise statistical significance (yuhong zhang and yunbo rao)biological network mining:indexing for similarity queries on biological networks (günhan gülsoy, md mahmudul hasan, yusuf kavurucu and tamer kahveci)theory and method of completion for a boolean regulatory network using observed data (takeyuki tamura and tatsuya akutsu)mining frequent subgraph patterns for classifying biological data (saeed salem)on the integration of prior knowledge in the inference of regulatory networks (catharina olsen, benjamin haibe-kains, john quackenbush and gianluca bontempi)classification, trend analysis and 3d medical images:classification and its application to drug-target prediction (jian-ping mei, chee-keong kwoh, peng yang and xiao-li li)characterization and prediction of human protein-protein interactions (yi xiong, dan syzmanski and daisuke kihara)trend analysis (wen-chuan xie, miao he and jake yue chen)data acquisition and preprocessing on three dimensional medical images (yuhua jiao, liang chen and jin chen)text mining and its biomedical applications:text mining in biomedicine and healthcare (hong-jie dai, chi-yang wu, richard tzong-han tsai and wen-lian hsu)learning to rank biomedical documents with only positive and unlabeled examples: a case study (mingzhu zhu, yi-fang brook wu, meghana samir vasavada and jason t l wang)automated mining of disease-specific protein interaction networks based on biomedical literature (rajesh chowdhary, boris r jankovic, rachel v stankowski, john a c archer, xiangliang zhang, xin gao, vladimir b bajic) readership: students, professionals, those who perform biological, medical and bioinformatics research. keywords:healthcare;data mining;biological data mining;protein interactions;gene regulation;text mining;biological literature mining;drug discovery;disease network;biological network;graph mining;sequence analysis;structure analysis;trend analysis;medical imageskey features:each chapter of this book will include a section to introduce a specific class of data mining techniques, which will be written in a tutorial style so that even non-computational readers such as biologists and healthcare researchers can appreciate themthe book will disseminate the impact research results and best practices of data mining approaches to the cross-disciplinary researchers and practitioners from both the data mining disciplines and the life sciences domains. the authors of the book will be well-known data mining experts, bioinformaticians and clinicianseach chapter will also provide a detailed description on how to apply the data mining techniques in real-world biological and clinical applications. thus, readers of this book can easily appreciate the computational techniques and how they can be used to address their own research issues

Data Mining Applications with R

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Author by : Yanchang Zhao, Yonghua Cen
Languange Used : English, France, Spanish, Italia and chinese
Page : 514
Isbn : 0124115209
Identifier : 9780124115200
Release : 2013-11-26
Publisher by : Academic Press
Category : Computers
Total Download : 5001045
Total Read : 4520655
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Description : Read Now Data Mining Applications With R by Yanchang Zhao, Yonghua Cen and you can download with pub, pdf, txt, doc, and more file format with free account. data mining applications with r is a great resource for researchers and professionals to understand the wide use of r, a free software environment for statistical computing and graphics, in solving different problems in industry. r is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. this book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. it is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. r code, data and color figures for the book are provided at the rdatamining.com website. helps data miners to learn to use r in their specific area of work and see how r can apply in different industries presents various case studies in real-world applications, which will help readers to apply the techniques in their work provides code examples and sample data for readers to easily learn the techniques by running the code by themselves

Handbook of Statistical Analysis and Data Mining Applications

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Author by : Robert Nisbet, Gary Miner, Ken Yale
Languange Used : English, France, Spanish, Italia and chinese
Page : 822
Isbn : 0124166458
Identifier : 9780124166455
Release : 2017-11-09
Publisher by : Elsevier
Category : Mathematics
Total Download : 1325487
Total Read : 7356722
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Description : Read Now Handbook Of Statistical Analysis And Data Mining Applications by Robert Nisbet, Gary Miner, Ken Yale and you can download with pub, pdf, txt, doc, and more file format with free account. handbook of statistical analysis and data mining applications, second edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. the handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. this book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. it has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. includes input by practitioners for practitioners includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models contains practical advice from successful real-world implementations brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Data Mining and Applications in Genomics

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Author by : Sio-Iong Ao
Languange Used : English, France, Spanish, Italia and chinese
Page : 152
Isbn : 1402089759
Identifier : 9781402089756
Release : 2008-09-25
Publisher by : Springer Science & Business Media
Category : Computers
Total Download : 2641491
Total Read : 8921960
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Description : Read Now Data Mining And Applications In Genomics by Sio-Iong Ao and you can download with pub, pdf, txt, doc, and more file format with free account. data mining and applications in genomics contains the data mining algorithms and their applications in genomics, with frontier case studies based on the recent and current works at the university of hong kong and the oxford university computing laboratory, university of oxford. it provides a systematic introduction to the use of data mining algorithms as an investigative tool for applications in genomics. data mining and applications in genomics offers state of the art of tremendous advances in data mining algorithms and applications in genomics and also serves as an excellent reference work for researchers and graduate students working on data mining algorithms and applications in genomics.

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 : 4833984
Total Read : 851412
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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.

INTRODUCTION TO DATA MINING WITH CASE STUDIES

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Author by : G. K. GUPTA
Languange Used : English, France, Spanish, Italia and chinese
Page : 536
Isbn : 8120350022
Identifier : 9788120350021
Release : 2014-06-28
Publisher by : PHI Learning Pvt. Ltd.
Category : Computers
Total Download : 5701917
Total Read : 1659484
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Description : Read Now Introduction To Data Mining With Case Studies by G. K. GUPTA and you can download with pub, pdf, txt, doc, and more file format with free account. the field of data mining provides techniques for automated discovery of valuable information from the accumulated data of computerized operations of enterprises. this book offers a clear and comprehensive introduction to both data mining theory and practice. it is written primarily as a textbook for the students of computer science, management, computer applications, and information technology. the book ensures that the students learn the major data mining techniques even if they do not have a strong mathematical background. the techniques include data pre-processing, association rule mining, supervised classification, cluster analysis, web data mining, search engine query mining, data warehousing and olap. to enhance the understanding of the concepts introduced, and to show how the techniques described in the book are used in practice, each chapter is followed by one or two case studies that have been published in scholarly journals. most case studies deal with real business problems (for example, marketing, e-commerce, crm). studying the case studies provides the reader with a greater insight into the data mining techniques. the book also provides many examples, review questions, multiple choice questions, chapter-end exercises and a good list of references and web resources especially those which are easy to understand and useful for students. a number of class projects have also been included.

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 : 1503568
Total Read : 8158736
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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

Data Mining Applications for Empowering Knowledge Societies

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Author by : Rahman, Hakikur
Languange Used : English, France, Spanish, Italia and chinese
Page : 356
Isbn : 1599046598
Identifier : 9781599046594
Release : 2008-07-31
Publisher by : IGI Global
Category : Technology & Engineering
Total Download : 4335568
Total Read : 3316114
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Description : Read Now Data Mining Applications For Empowering Knowledge Societies by Rahman, Hakikur and you can download with pub, pdf, txt, doc, and more file format with free account. presents an overview of the main issues of data mining, including its classification, regression, clustering, and ethical issues. provides readers with knowledge enhancing processes as well as a wide spectrum of data mining applications.

Multimedia Data Mining A Systematic Introduction to Concepts and Theory

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Author by : Zhongfei Zhang, Ruofei Zhang
Languange Used : English, France, Spanish, Italia and chinese
Page : 320
Isbn : 9781584889670
Identifier : 1584889675
Release : 2008-12-02
Publisher by : CRC Press
Category : Computers
Total Download : 3089307
Total Read : 4647189
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Description : Read Now Multimedia Data Mining by Zhongfei Zhang, Ruofei Zhang and you can download with pub, pdf, txt, doc, and more file format with free account. collecting the latest developments in the field, multimedia data mining: a systematic introduction to concepts and theory defines multimedia data mining, its theory, and its applications. two of the most active researchers in multimedia data mining explore how this young area has rapidly developed in recent years. the book first discusses the theoretical foundations of multimedia data mining, presenting commonly used feature representation, knowledge representation, statistical learning, and soft computing techniques. it then provides application examples that showcase the great potential of multimedia data mining technologies. in this part, the authors show how to develop a semantic repository training method and a concept discovery method in an imagery database. they demonstrate how knowledge discovery helps achieve the goal of imagery annotation. the authors also describe an effective solution to large-scale video search, along with an application of audio data classification and categorization. this novel, self-contained book examines how the merging of multimedia and data mining research can promote the understanding and advance the development of knowledge discovery in multimedia data.

Discovering Knowledge in Data An Introduction to Data Mining

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Author by : Daniel T. Larose, Chantal D. Larose
Languange Used : English, France, Spanish, Italia and chinese
Page : 336
Isbn : 1118873572
Identifier : 9781118873571
Release : 2014-06-02
Publisher by : John Wiley & Sons
Category : Computers
Total Download : 2557693
Total Read : 2934459
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Description : Read Now Discovering Knowledge In Data by Daniel T. Larose, Chantal D. Larose and you can download with pub, pdf, txt, doc, and more file format with free account. the field of data mining lies at the confluence of predictive analytics, statistical analysis, and business intelligence. due to the ever-increasing complexity and size of data sets and the wide range of applications in computer science, business, and health care, the process of discovering knowledge in data is more relevant than ever before. this book provides the tools needed to thrive in today’s big data world. the author demonstrates how to leverage a company’s existing databases to increase profits and market share, and carefully explains the most current data science methods and techniques. the reader will “learn data mining by doing data mining”. by adding chapters on data modelling preparation, imputation of missing data, and multivariate statistical analysis, discovering knowledge in data, second edition remains the eminent reference on data mining. the second edition of a highly praised, successful reference on data mining, with thorough coverage of big data applications, predictive analytics, and statistical analysis. includes new chapters on multivariate statistics, preparing to model the data, and imputation of missing data, and an appendix on data summarization and visualization offers extensive coverage of the r statistical programming language contains 280 end-of-chapter exercises includes a companion website for university instructors who adopt the book

Data Mining in Agriculture

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Author by : Antonio Mucherino, Petraq Papajorgji, Panos M. Pardalos
Languange Used : English, France, Spanish, Italia and chinese
Page : 274
Isbn : 038788615X
Identifier : 9780387886152
Release : 2009-09-22
Publisher by : Springer Science & Business Media
Category : Mathematics
Total Download : 5953236
Total Read : 279933
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Description : Read Now Data Mining In Agriculture by Antonio Mucherino, Petraq Papajorgji, Panos M. Pardalos and you can download with pub, pdf, txt, doc, and more file format with free account. data mining in agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields. this book presents both theoretical and practical insights with a focus on presenting the context of each data mining technique rather intuitively with ample concrete examples represented graphically and with algorithms written in matlab®.