Mining Imperfect Data
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Mining Imperfect Data
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Author : Ronald K. Pearson
language : en
Publisher: SIAM
Release Date : 2005-04-01
Mining Imperfect Data written by Ronald K. Pearson and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-04-01 with Computers categories.
This book discusses the problems that can occur in data mining, including their sources, consequences, detection and treatment.
Mining Imperfect Data
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Author : Ronald K. Pearson
language : en
Publisher: SIAM
Release Date : 2020-09-10
Mining Imperfect Data written by Ronald K. Pearson and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-10 with Computers categories.
It has been estimated that as much as 80% of the total effort in a typical data analysis project is taken up with data preparation, including reconciling and merging data from different sources, identifying and interpreting various data anomalies, and selecting and implementing appropriate treatment strategies for the anomalies that are found. This book focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them. As both data sources and free, open-source data analysis software environments proliferate, more people and organizations are motivated to extract useful insights and information from data of many different kinds (e.g., numerical, categorical, and text). The book emphasizes the range of open-source tools available for identifying and treating data anomalies, mostly in R but also with several examples in Python. Mining Imperfect Data: With Examples in R and Python, Second Edition presents a unified coverage of 10 different types of data anomalies (outliers, missing data, inliers, metadata errors, misalignment errors, thin levels in categorical variables, noninformative variables, duplicated records, coarsening of numerical data, and target leakage). It includes an in-depth treatment of time-series outliers and simple nonlinear digital filtering strategies for dealing with them, and it provides a detailed introduction to several useful mathematical characteristics of important data characterizations that do not appear to be widely known among practitioners, such as functional equations and key inequalities. While this book is primarily for data scientists, researchers in a variety of fields—namely statistics, machine learning, physics, engineering, medicine, social sciences, economics, and business—will also find it useful.
Mining Imperfect Data
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Author : Ronald K. Pearson
language : en
Publisher:
Release Date : 2020
Mining Imperfect Data written by Ronald K. Pearson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Data mining categories.
"This second edition of Mining Imperfect Data reflects changes in the size and nature of the datasets commonly encountered for analysis, and the evolution of the tools now available for this analysis"--
Data Mining In Public And Private Sectors Organizational And Government Applications
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Author : Syvajarvi, Antti
language : en
Publisher: IGI Global
Release Date : 2010-06-30
Data Mining In Public And Private Sectors Organizational And Government Applications written by Syvajarvi, Antti and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-30 with Computers categories.
The need for both organizations and government agencies to generate, collect, and utilize data in public and private sector activities is rapidly increasing, placing importance on the growth of data mining applications and tools. Data Mining in Public and Private Sectors: Organizational and Government Applications explores the manifestation of data mining and how it can be enhanced at various levels of management. This innovative publication provides relevant theoretical frameworks and the latest empirical research findings useful to governmental agencies, practicing managers, and academicians.
Principles Of Data Mining
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Author : David J. Hand
language : en
Publisher: MIT Press
Release Date : 2001-08-17
Principles Of Data Mining written by David J. Hand and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-08-17 with Computers categories.
The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
Web Data Mining
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Author : Bing Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-25
Web Data Mining written by Bing Liu and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-25 with Computers categories.
Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text. The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.
Applied Computational Intelligence
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Author : Da Ruan
language : en
Publisher: World Scientific
Release Date : 2004
Applied Computational Intelligence written by Da Ruan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
FLINS, originally an acronym for OC Fuzzy Logic and Intelligent technologies in Nuclear ScienceOCO, has now been extended to include computational intelligent systems for applied research. FLINS 2004, is the sixth in a series of international conferences, covers state-of-the-art research and development in applied computational intelligence for applied research in general and for power/nuclear engineering in particular. This book presents the latest research trends and future research directions in the field. The proceedings have been selected for coverage in: . OCo Index to Scientific & Technical Proceedings- (ISTP / ISI Proceedings). OCo Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings). OCo CC Proceedings OCo Engineering & Physical Sciences."
Information Processing And Management Of Uncertainty In Knowledge Based Systems Theory And Foundations
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Author : Jesús Medina
language : en
Publisher: Springer
Release Date : 2018-05-30
Information Processing And Management Of Uncertainty In Knowledge Based Systems Theory And Foundations written by Jesús Medina and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-30 with Computers categories.
This three volume set (CCIS 853-855) constitutes the proceedings of the 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2017, held in Cádiz, Spain, in June 2018. The 193 revised full papers were carefully reviewed and selected from 383 submissions. The papers are organized in topical sections on advances on explainable artificial intelligence; aggregation operators, fuzzy metrics and applications; belief function theory and its applications; current techniques to model, process and describe time series; discrete models and computational intelligence; formal concept analysis and uncertainty; fuzzy implication functions; fuzzy logic and artificial intelligence problems; fuzzy mathematical analysis and applications; fuzzy methods in data mining and knowledge discovery; fuzzy transforms: theory and applications to data analysis and image processing; imprecise probabilities: foundations and applications; mathematical fuzzy logic, mathematical morphology; measures of comparison and entropies for fuzzy sets and their extensions; new trends in data aggregation; pre-aggregation functions and generalized forms of monotonicity; rough and fuzzy similarity modelling tools; soft computing for decision making in uncertainty; soft computing in information retrieval and sentiment analysis; tri-partitions and uncertainty; decision making modeling and applications; logical methods in mining knowledge from big data; metaheuristics and machine learning; optimization models for modern analytics; uncertainty in medicine; uncertainty in Video/Image Processing (UVIP).
Networked Digital Technologies
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Author : Rachid Benlamri
language : en
Publisher: Springer
Release Date : 2012-06-02
Networked Digital Technologies written by Rachid Benlamri and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-02 with Computers categories.
This two-volume-set (CCIS 293 and CCIS 294) constitutes the refereed proceedings of the International Conference on Networked Digital Technologies, NDT 2012, held in Dubai, UAE, in April 2012. The 96 papers presented in the two volumes were carefully reviewed and selected from 228 submissions. The papers are organized in topical sections on collaborative systems for e-sciences; context-aware processing and ubiquitous systems; data and network mining; grid and cloud computing; information and data management; intelligent agent-based systems; internet modeling and design; mobile, ad hoc and sensor network management; peer-to-peer social networks; quality of service for networked systems; semantic Web and ontologies; security and access control; signal processing and computer vision for networked systems; social networks; Web services.
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.