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Pocket Data Mining
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Book Synopsis Pocket Data Mining by : Mohamed Medhat Gaber
Download or read book Pocket Data Mining written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2013-10-19 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.
Book Synopsis Pocket Data Mining by : Mohamed Medhat Gaber
Download or read book Pocket Data Mining written by Mohamed Medhat Gaber and published by . This book was released on 2013-11-30 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Clinical Data-Mining by : Irwin Epstein
Download or read book Clinical Data-Mining written by Irwin Epstein and published by Oxford University Press. This book was released on 2010 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clinical Data-Mining (CDM) involves the conceptualization, extraction, analysis, and interpretation of available clinical data for practice knowledge-building, clinical decision-making and practitioner reflection. Depending upon the type of data mined, CDM can be qualitative or quantitative; it is generally retrospective, but may be meaningfully combined with original data collection.Any research method that relies on the contents of case records or information systems data inevitably has limitations, but with proper safeguards these can be minimized. Among CDM's strengths however, are that it is unobtrusive, inexpensive, presents little risk to research subjects, and is ethically compatible with practitioner value commitments. When conducted by practitioners, CDM yields conceptual as well as data-driven insight into their own practice- and program-generated questions.This pocket guide, from a seasoned practice-based researcher, covers all the basics of conducting practitioner-initiated CDM studies or CDM doctoral dissertations, drawing extensively on published CDM studies and completed CDM dissertations from multiple social work settings in the United States, Australia, Israel, Hong Kong and the United Kingdom. In addition, it describes consulting principles for researchers interested in forging collaborative university-agency CDM partnerships, making it a practical tool for novice practitioner-researchers and veteran academic-researchers alike.As such, this book is an exceptional guide both for professionals conducting practice-based research as well as for social work faculty seeking an evidence-informed approach to practice-research integration.
Book Synopsis The Handbook of Data Mining by : Nong Ye
Download or read book The Handbook of Data Mining written by Nong Ye and published by CRC Press. This book was released on 2003-04-01 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: Created with the input of a distinguished International Board of the foremost authorities in data mining from academia and industry, The Handbook of Data Mining presents comprehensive coverage of data mining concepts and techniques. Algorithms, methodologies, management issues, and tools are all illustrated through engaging examples and real-world applications to ease understanding of the materials. This book is organized into three parts. Part I presents various data mining methodologies, concepts, and available software tools for each methodology. Part II addresses various issues typically faced in the management of data mining projects and tips on how to maximize outcome utility. Part III features numerous real-world applications of these techniques in a variety of areas, including human performance, geospatial, bioinformatics, on- and off-line customer transaction activity, security-related computer audits, network traffic, text and image, and manufacturing quality. This Handbook is ideal for researchers and developers who want to use data mining techniques to derive scientific inferences where extensive data is available in scattered reports and publications. It is also an excellent resource for graduate-level courses on data mining and decision and expert systems methodology.
Book Synopsis Data Pipelines Pocket Reference by : James Densmore
Download or read book Data Pipelines Pocket Reference written by James Densmore and published by O'Reilly Media. This book was released on 2021-02-10 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data pipelines are the foundation for success in data analytics. Moving data from numerous diverse sources and transforming it to provide context is the difference between having data and actually gaining value from it. This pocket reference defines data pipelines and explains how they work in today's modern data stack. You'll learn common considerations and key decision points when implementing pipelines, such as batch versus streaming data ingestion and build versus buy. This book addresses the most common decisions made by data professionals and discusses foundational concepts that apply to open source frameworks, commercial products, and homegrown solutions. You'll learn: What a data pipeline is and how it works How data is moved and processed on modern data infrastructure, including cloud platforms Common tools and products used by data engineers to build pipelines How pipelines support analytics and reporting needs Considerations for pipeline maintenance, testing, and alerting
Book Synopsis Data Mining For Dummies by : Meta S. Brown
Download or read book Data Mining For Dummies written by Meta S. Brown and published by John Wiley & Sons. This book was released on 2014-09-29 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business's entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn't take a data scientist to gain this advantage, and empowers average business people to start shaping a process relevant to their business's needs. In this book, you'll learn the hows and whys of mining to the depths of your data, and how to make the case for heavier investment into data mining capabilities. The book explains the details of the knowledge discovery process including: Model creation, validity testing, and interpretation Effective communication of findings Available tools, both paid and open-source Data selection, transformation, and evaluation Data Mining for Dummies takes you step-by-step through a real-world data-mining project using open-source tools that allow you to get immediate hands-on experience working with large amounts of data. You'll gain the confidence you need to start making data mining practices a routine part of your successful business. If you're serious about doing everything you can to push your company to the top, Data Mining for Dummies is your ticket to effective data mining.
Book Synopsis Foundations of Intelligent Systems by : Marzena Kryszkiewics
Download or read book Foundations of Intelligent Systems written by Marzena Kryszkiewics and published by Springer Science & Business Media. This book was released on 2011-06-22 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 19th International Symposium on Methodologies for Intelligent Systems, ISMIS 2011, held in Warsaw, Poland, in June 2011. The 71 revised papers presented together with 3 invited papers were carefully reviewed and selected from 131 submissions. The papers are organized in topical sections on rough sets - in memoriam Zdzisław Pawlik, challenges in knowledge discovery and data mining - in memoriam Jan Żytkov, social networks, multi-agent systems, theoretical backgrounds of AI, machine learning, data mining, mining in databases and warehouses, text mining, theoretical issues and applications of intelligent web, application of intelligent systems in sound processing, intelligent applications in biology and medicine, fuzzy sets theory and applications, intelligent systems, tools and applications, and contest on music information retrieval.
Book Synopsis Big Data Analysis: New Algorithms for a New Society by : Nathalie Japkowicz
Download or read book Big Data Analysis: New Algorithms for a New Society written by Nathalie Japkowicz and published by Springer. This book was released on 2015-12-16 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.
Book Synopsis Advances in Intelligent Data Analysis X by : João Gama
Download or read book Advances in Intelligent Data Analysis X written by João Gama and published by Springer. This book was released on 2011-10-25 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Conference on Intelligent Data Analysis, IDA 2011, held in Porto, Portugal, in October 2011. The 19 revised full papers and 16 revised poster papers resented together with 3 invited papers were carefully reviewed and selected from 73 submissions. All current aspects of intelligent data analysis are addressed, particularly intelligent support for modeling and analyzing complex, dynamical systems. The papers offer intelligent support for understanding evolving scientific and social systems including data collection and acquisition, such as crowd sourcing; data cleaning, semantics and markup; searching for data and assembling datasets from multiple sources; data processing, including workflows, mixed-initiative data analysis, and planning; data and information fusion; incremental, mixed-initiative model development, testing and revision; and visualization and dissemination of results; etc.
Author :Abdelkader Hameurlain Publisher :Springer Science & Business Media ISBN 13 :3642281478 Total Pages :230 pages Book Rating :4.6/5 (422 download)
Book Synopsis Transactions on Large-Scale Data- and Knowledge-Centered Systems V by : Abdelkader Hameurlain
Download or read book Transactions on Large-Scale Data- and Knowledge-Centered Systems V written by Abdelkader Hameurlain and published by Springer Science & Business Media. This book was released on 2012-02-10 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This fifth issue of the LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems offers nine full-length focusing on such hot topics as data management, knowledge discovery, and knowledge processing.
Book Synopsis Machine Learning Pocket Reference by : Matt Harrison
Download or read book Machine Learning Pocket Reference written by Matt Harrison and published by "O'Reilly Media, Inc.". This book was released on 2019-08-27 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
Book Synopsis Biological Data Mining by : Jake Y. Chen
Download or read book Biological Data Mining written by Jake Y. Chen and published by CRC Press. This book was released on 2009-09-01 with total page 733 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Proceedings of the Fifth SIAM International Conference on Data Mining by : Hillol Kargupta
Download or read book Proceedings of the Fifth SIAM International Conference on Data Mining written by Hillol Kargupta and published by SIAM. This book was released on 2005-04-01 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.
Book Synopsis Rule Based Systems for Big Data by : Han Liu
Download or read book Rule Based Systems for Big Data written by Han Liu and published by Springer. This book was released on 2015-09-09 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.
Book Synopsis Data Mining Methods and Applications by : Kenneth D. Lawrence
Download or read book Data Mining Methods and Applications written by Kenneth D. Lawrence and published by CRC Press. This book was released on 2007-12-22 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: With today’s information explosion, many organizations are now able to access a wealth of valuable data. Unfortunately, most of these organizations find they are ill-equipped to organize this information, let alone put it to work for them. Gain a Competitive Advantage Employ data mining in research and forecasting Build models with data management tools and methodology optimization Gain sophisticated breakdowns and complex analysis through multivariate, evolutionary, and neural net methods Learn how to classify data and maintain quality Transform Data into Business Acumen Data Mining Methods and Applications supplies organizations with the data management tools that will allow them to harness the critical facts and figures needed to improve their bottom line. Drawing from finance, marketing, economics, science, and healthcare, this forward thinking volume: Demonstrates how the transformation of data into business intelligence is an essential aspect of strategic decision-making Emphasizes the use of data mining concepts in real-world scenarios with large database components Focuses on data mining and forecasting methods in conducting market research
Book Synopsis Big Data by : Viktor Mayer-Schönberger
Download or read book Big Data written by Viktor Mayer-Schönberger and published by Houghton Mifflin Harcourt. This book was released on 2013 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.
Book Synopsis Advances in Knowledge Discovery in Databases by : Animesh Adhikari
Download or read book Advances in Knowledge Discovery in Databases written by Animesh Adhikari and published by Springer. This book was released on 2014-12-27 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances in Knowledge discovery in databases (KDD) with a focus on the areas of market basket database, time-stamped databases and multiple related databases. Various interesting and intelligent algorithms are reported on data mining tasks. A large number of association measures are presented, which play significant roles in decision support applications. This book presents, discusses and contrasts new developments in mining time-stamped data, time-based data analyses, the identification of temporal patterns, the mining of multiple related databases, as well as local patterns analysis.
