Domain Driven Data Mining

Domain Driven Data Mining PDF

Author: Longbing Cao

Publisher: Springer Science & Business Media

Published: 2010-01-08

Total Pages: 251

ISBN-13: 1441957375

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This book offers state-of the-art research and development outcomes on methodologies, techniques, approaches and successful applications in domain driven, actionable knowledge discovery. It bridges the gap between business expectations and research output.

Data Mining for Business Applications

Data Mining for Business Applications PDF

Author: Longbing Cao

Publisher: Springer Science & Business Media

Published: 2008-10-03

Total Pages: 310

ISBN-13: 0387794204

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Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

Domain Driven Data Mining A Complete Guide - 2020 Edition

Domain Driven Data Mining A Complete Guide - 2020 Edition PDF

Author: Gerardus Blokdyk

Publisher: 5starcooks

Published: 2020-03

Total Pages: 308

ISBN-13: 9781867339335

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How will success or failure be measured? How do you stay inspired? Did you tackle the cause or the symptom? Is there any additional Domain driven data mining definition of success? What are the business goals Domain driven data mining is aiming to achieve? This one-of-a-kind Domain Driven Data Mining self-assessment will make you the trusted Domain Driven Data Mining domain expert by revealing just what you need to know to be fluent and ready for any Domain Driven Data Mining challenge. How do I reduce the effort in the Domain Driven Data Mining work to be done to get problems solved? How can I ensure that plans of action include every Domain Driven Data Mining task and that every Domain Driven Data Mining outcome is in place? How will I save time investigating strategic and tactical options and ensuring Domain Driven Data Mining costs are low? How can I deliver tailored Domain Driven Data Mining advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Domain Driven Data Mining essentials are covered, from every angle: the Domain Driven Data Mining self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Domain Driven Data Mining outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Domain Driven Data Mining practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Domain Driven Data Mining are maximized with professional results. Your purchase includes access details to the Domain Driven Data Mining self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Domain Driven Data Mining Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Proactive Data Mining with Decision Trees

Proactive Data Mining with Decision Trees PDF

Author: Haim Dahan

Publisher: Springer Science & Business Media

Published: 2014-02-14

Total Pages: 94

ISBN-13: 1493905392

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This book explores a proactive and domain-driven method to classification tasks. This novel proactive approach to data mining not only induces a model for predicting or explaining a phenomenon, but also utilizes specific problem/domain knowledge to suggest specific actions to achieve optimal changes in the value of the target attribute. In particular, the authors suggest a specific implementation of the domain-driven proactive approach for classification trees. The book centers on the core idea of moving observations from one branch of the tree to another. It introduces a novel splitting criterion for decision trees, termed maximal-utility, which maximizes the potential for enhancing profitability in the output tree. Two real-world case studies, one of a leading wireless operator and the other of a major security company, are also included and demonstrate how applying the proactive approach to classification tasks can solve business problems. Proactive Data Mining with Decision Trees is intended for researchers, practitioners and advanced-level students.

Intelligent Knowledge

Intelligent Knowledge PDF

Author: Yong Shi

Publisher: Springer

Published: 2015-05-08

Total Pages: 160

ISBN-13: 3662461935

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This book is mainly about an innovative and fundamental method called “intelligent knowledge” to bridge the gap between data mining and knowledge management, two important fields recognized by the information technology (IT) community and business analytics (BA) community respectively. The book includes definitions of the “first-order” analytic process, “second-order” analytic process and intelligent knowledge, which have not formally been addressed by either data mining or knowledge management. Based on these concepts, which are especially important in connection with the current Big Data movement, the book describes a framework of domain-driven intelligent knowledge discovery. To illustrate its technical advantages for large-scale data, the book employs established approaches, such as Multiple Criteria Programming, Support Vector Machine and Decision Tree to identify intelligent knowledge incorporated with human knowledge. The book further shows its applicability by means of real-life data analyses in the contexts of internet business and traditional Chinese medicines.

Data-Driven Science and Engineering

Data-Driven Science and Engineering PDF

Author: Steven L. Brunton

Publisher: Cambridge University Press

Published: 2022-05-05

Total Pages: 615

ISBN-13: 1009098489

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A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.