Analisi Dei Dati E Data Mining
DOWNLOAD
Download Analisi Dei Dati E Data Mining PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Analisi Dei Dati E Data Mining book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Analisi Dei Dati E Data Mining Per Le Decisioni Aziendali
DOWNLOAD
Author : Sergio Zani
language : it
Publisher: Giuffrè Editore
Release Date : 2007
Analisi Dei Dati E Data Mining Per Le Decisioni Aziendali written by Sergio Zani and has been published by Giuffrè Editore this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Mathematics categories.
Analisi Dei Dati E Data Mining
DOWNLOAD
Author : A. Azzalini
language : it
Publisher: Springer Science & Business Media
Release Date : 2009-05-12
Analisi Dei Dati E Data Mining written by A. Azzalini 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 2009-05-12 with Business & Economics categories.
Negli ultimi dieci anni c’è stata un’ampia fase dell’innovazione tecnologica che ha portato alla diffusione di grandi quantità di dati in diversi campi applicativi. Le aziende in primo luogo hanno a disposizione moltissimi elementi informativi riguardanti i loro clienti, ma anche nella medicina, nella genetica, nella biologia, e in molti altri ambienti applicativi sono ora a disposizioni grandi masse di dati. Tale realtà porta con sé la necessità di sviluppare e conoscere nuovi strumenti di analisi statistica. In questo contesto molti strumenti e metodi di analisi hanno origini diverse, in particolare dalla statistica e dal machine learning, ma condividono molti aspetti. Questo libro descrive i concetti più importanti di queste aree in un’impostazione unificata. Seppure l’approccio sia statistico, l’enfasi è sui concetti piuttosto che sulla formulazione matematica. Vengono presentati molti esempi corredati da un’ampia varietà di illustrazioni grafiche. Il libro dovrebbe quindi costituire un utile strumento per gli statistici e per chiunque altro è interessato al data mining sia nel mondo aziendale che in quello scientifico.
Data Analysis And Data Mining
DOWNLOAD
Author : Adelchi Azzalini
language : en
Publisher: OUP USA
Release Date : 2012-04-23
Data Analysis And Data Mining written by Adelchi Azzalini and has been published by OUP USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-23 with Business & Economics categories.
This book introduces the specific statistical methods and models involved in data mining, targeting students and professionals with a a basic knowledge of statistical reasoning.
Analysis Of Data And Processes From Standard To Realtime Data Mining
DOWNLOAD
Author : Armenak Barsegian
language : en
Publisher:
Release Date : 2014
Analysis Of Data And Processes From Standard To Realtime Data Mining written by Armenak Barsegian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.
Customer And Business Analytics
DOWNLOAD
Author : Daniel S. Putler
language : en
Publisher: CRC Press
Release Date : 2015-09-15
Customer And Business Analytics written by Daniel S. Putler and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-15 with Business & Economics categories.
Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.
Data Analysis And Data Mining
DOWNLOAD
Author : Adelchi Azzalini
language : en
Publisher: Oxford University Press
Release Date : 2012-04-23
Data Analysis And Data Mining written by Adelchi Azzalini and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04-23 with Business & Economics categories.
An introduction to statistical data mining, Data Analysis and Data Mining is both textbook and professional resource. Assuming only a basic knowledge of statistical reasoning, it presents core concepts in data mining and exploratory statistical models to students and professional statisticians-both those working in communications and those working in a technological or scientific capacity-who have a limited knowledge of data mining. This book presents key statistical concepts by way of case studies, giving readers the benefit of learning from real problems and real data. Aided by a diverse range of statistical methods and techniques, readers will move from simple problems to complex problems. Through these case studies, authors Adelchi Azzalini and Bruno Scarpa explain exactly how statistical methods work; rather than relying on the "push the button" philosophy, they demonstrate how to use statistical tools to find the best solution to any given problem. Case studies feature current topics highly relevant to data mining, such web page traffic; the segmentation of customers; selection of customers for direct mail commercial campaigns; fraud detection; and measurements of customer satisfaction. Appropriate for both advanced undergraduate and graduate students, this much-needed book will fill a gap between higher level books, which emphasize technical explanations, and lower level books, which assume no prior knowledge and do not explain the methodology behind the statistical operations.
Statistical Data Analytics
DOWNLOAD
Author : Walter W. Piegorsch
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-21
Statistical Data Analytics written by Walter W. Piegorsch 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 2015-08-21 with Mathematics categories.
Statistical Data Analytics Statistical Data Analytics Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development and interactive, linkable internet software. This book presents a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and probability. It includes an overview of probability and statistical distributions, basics of data manipulation and visualization, and the central components of standard statistical inferences. The majority of the text extends beyond these introductory topics, however, to supervised learning in linear regression, generalized linear models, and classification analytics. Finally, unsupervised learning via dimension reduction, cluster analysis, and market basket analysis are introduced. Extensive examples using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others. Statistical Data Analytics: Focuses on methods critically used in data mining and statistical informatics. Coherently describes the methods at an introductory level, with extensions to selected intermediate and advanced techniques. Provides informative, technical details for the highlighted methods. Employs the open-source R language as the computational vehicle – along with its burgeoning collection of online packages – to illustrate many of the analyses contained in the book. Concludes each chapter with a range of interesting and challenging homework exercises using actual data from a variety of informatic application areas. This book will appeal as a classroom or training text to intermediate and advanced undergraduates, and to beginning graduate students, with sufficient background in calculus and matrix algebra. It will also serve as a source-book on the foundations of statistical informatics and data analytics to practitioners who regularly apply statistical learning to their modern data.
Exploratory Data Mining And Data Cleaning
DOWNLOAD
Author : Tamraparni Dasu
language : en
Publisher: John Wiley & Sons
Release Date : 2003-08-01
Exploratory Data Mining And Data Cleaning written by Tamraparni Dasu 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 2003-08-01 with Mathematics categories.
Written for practitioners of data mining, data cleaning and database management. Presents a technical treatment of data quality including process, metrics, tools and algorithms. Focuses on developing an evolving modeling strategy through an iterative data exploration loop and incorporation of domain knowledge. Addresses methods of detecting, quantifying and correcting data quality issues that can have a significant impact on findings and decisions, using commercially available tools as well as new algorithmic approaches. Uses case studies to illustrate applications in real life scenarios. Highlights new approaches and methodologies, such as the DataSphere space partitioning and summary based analysis techniques. Exploratory Data Mining and Data Cleaning will serve as an important reference for serious data analysts who need to analyze large amounts of unfamiliar data, managers of operations databases, and students in undergraduate or graduate level courses dealing with large scale data analys is and data mining.
Discovering Knowledge In Data
DOWNLOAD
Author : Daniel T. Larose
language : en
Publisher:
Release Date : 2005
Discovering Knowledge In Data written by Daniel T. Larose and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Data mining categories.
Responsible Analytics And Data Mining In Education
DOWNLOAD
Author : Badrul H. Khan
language : en
Publisher: Routledge
Release Date : 2018-12-07
Responsible Analytics And Data Mining In Education written by Badrul H. Khan and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Computers categories.
Winner of two Outstanding Book Awards from the Association of Educational Communications and Technology (Culture, Learning, & Technology and Systems Thinking & Change divisions)! Rapid advancements in our ability to collect, process, and analyze massive amounts of data along with the widespread use of online and blended learning platforms have enabled educators at all levels to gain new insights into how people learn. Responsible Analytics and Data Mining in Education addresses the thoughtful and purposeful navigation, evaluation, and implementation of these emerging forms of educational data analysis. Chapter authors from around the world explore how data analytics can be used to improve course and program quality; how the data and its interpretations may inadvertently impact students, faculty, and institutions; the quality and reliability of data, as well as the accuracy of data-based decisions; ethical implications surrounding the collection, distribution, and use of student-generated data; and more. This volume unpacks and explores this complex issue through a systematic framework whose dimensions address the issues that must be considered before implementation of a new initiative or program.