Mining Library: Details of practical mining, [c1916 PDF Download
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Author:
Publisher:
ISBN:
Category : Mineral industries
Languages : en
Pages : 564
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Book Description
Author: Nagiza F. Samatova
Publisher: CRC Press
ISBN: 1439860858
Category : Business & Economics
Languages : en
Pages : 495
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Book Description
Discover Novel and Insightful Knowledge from Data Represented as a GraphPractical Graph Mining with R presents a "do-it-yourself" approach to extracting interesting patterns from graph data. It covers many basic and advanced techniques for the identification of anomalous or frequently recurring patterns in a graph, the discovery of groups or cluste
Author: A R C. Matuska
Publisher:
ISBN: 9781612049526
Category : Technology & Engineering
Languages : en
Pages : 356
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Book Description
Where does a wannabe miner or established individual operator get the information to create a small yet highly profitable mining company? When author A R C Matuska searched for simple, practical mining books and information about the industry, he found high-powered studies, academic theses and computer modeling. In short, nothing of use to the small, practical mine operator. The best information he found was in booklets aimed at ex-servicemen after World War II, encouraging them to take up mining in the British colonies in Africa. Since then, there has not been much written in such a useful and practical manner. To answer this need, a veritable goldmine of information is included in the book Practical Mining and Gold Processing for the Small Scale Operator. Where does a newcomer to the industry find out how to sample and calculate a potential resource and plan his mining business? Where does he get the information to run a small ball mill or stamp mill? How does he set up and dress a simple amalgam plate, retort some amalgam or make up a retort, and calculate the percentage of gold in bullion? Where does a small operator find out how to set up a low-cost cyanide plant and its running procedures? And how does he improve mining and blasting efficiencies? This book provides practical applications and solutions to get you started in one of the most diverse, profitable and interesting industries. It is indexed in detail so information can be easily found without sifting through realms of data. A R C Matuska is a career miner. He owns and consults for several mining properties in East and Central Africa. Publisher's website: http: //sbpra.com/ARCMatuska
Author: Gary Miner
Publisher: Academic Press
ISBN: 012386979X
Category : Computers
Languages : en
Pages : 1096
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Book Description
"The world contains an unimaginably vast amount of digital information which is getting ever vaster ever more rapidly. This makes it possible to do many things that previously could not be done: spot business trends, prevent diseases, combat crime and so on. Managed well, the textual data can be used to unlock new sources of economic value, provide fresh insights into science and hold governments to account. As the Internet expands and our natural capacity to process the unstructured text that it contains diminishes, the value of text mining for information retrieval and search will increase dramatically. This comprehensive professional reference brings together all the information, tools and methods a professional will need to efficiently use text mining applications and statistical analysis. The Handbook of Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications presents a comprehensive how- to reference that shows the user how to conduct text mining and statistically analyze results. In addition to providing an in-depth examination of core text mining and link detection tools, methods and operations, the book examines advanced preprocessing techniques, knowledge representation considerations, and visualization approaches. Finally, the book explores current real-world, mission-critical applications of text mining and link detection using real world example tutorials in such varied fields as corporate, finance, business intelligence, genomics research, and counterterrorism activities"--
Author: Ian H. Witten
Publisher: Elsevier
ISBN: 0080890369
Category : Computers
Languages : en
Pages : 665
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Book Description
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. - Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects - Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods - Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization
Author: Sang Suh
Publisher: Jones & Bartlett Publishers
ISBN: 0763785873
Category : Computers
Languages : en
Pages : 436
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Book Description
Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.
Author: Jr., Monte F. Hancock
Publisher: CRC Press
ISBN: 1439868379
Category : Computers
Languages : en
Pages : 304
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Book Description
Used by corporations, industry, and government to inform and fuel everything from focused advertising to homeland security, data mining can be a very useful tool across a wide range of applications. Unfortunately, most books on the subject are designed for the computer scientist and statistical illuminati and leave the reader largely adrift in tech
Author: Andrea Ahlemeyer-Stubbe
Publisher: John Wiley & Sons
ISBN: 1118763378
Category : Mathematics
Languages : en
Pages : 323
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Book Description
Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly approach to data mining methods, covering the typical uses to which it is applied. The methodology is complemented by case studies to create a versatile reference book, allowing readers to look for specific methods as well as for specific applications. The book is formatted to allow statisticians, computer scientists, and economists to cross-reference from a particular application or method to sectors of interest.
Author: Sholom M. Weiss
Publisher: Morgan Kaufmann
ISBN: 9781558604032
Category : Computers
Languages : en
Pages : 244
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Book Description
This book is the first technical guide to provide a complete, generalized road map for developing data-mining applications, together with advice on performing these large-scale, open-ended analyses for real-world data warehouses.
Author: Chandrika Kamath
Publisher: SIAM
ISBN: 0898717698
Category : Mathematics
Languages : en
Pages : 295
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Book Description
Chandrika Kamath describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains. Starting with a survey of analysis problems in different applications, it identifies the common themes across these domains.
Author: Ian H. Witten
Publisher: Morgan Kaufmann
ISBN: 9781558605527
Category : Computers
Languages : en
Pages : 414
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Book Description
This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large collections of data. Complementing the book's instruction is fully functional machine learning software.
