Fundamentos de minería de datos PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Fundamentos de minería de datos PDF full book. Access full book title Fundamentos de minería de datos by Rodríguez Rodríguez, Jorge Enrique. Download full books in PDF and EPUB format.
Author: Rodríguez Rodríguez, Jorge Enrique
Publisher: Editorial Universidad Distrital Francisco José de Caldas. Editorial UD
ISBN: 9587875524
Category : Computers
Languages : es
Pages : 195
Get Book Here
Book Description
El primer capítulo presenta conceptos, áreas, aplicaciones, tareas y otras disciplinas con las cuales se relaciona la minería de datos; en el segundo se describe el pre procesamiento de datos; el tercero introduce al lector en una tarea de minería de datos que centra su aplicación en el análisis de mercadeo; el cuarto está orientado a la predicción de datos, haciendo énfasis en clasificación y regresión; en el quinto muestra una de las tareas más representativas de minería de los datos: la agrupación por datos.
Author: Rodríguez Rodríguez, Jorge Enrique
Publisher: Editorial Universidad Distrital Francisco José de Caldas. Editorial UD
ISBN: 9587875524
Category : Computers
Languages : es
Pages : 195
Get Book Here
Book Description
El primer capítulo presenta conceptos, áreas, aplicaciones, tareas y otras disciplinas con las cuales se relaciona la minería de datos; en el segundo se describe el pre procesamiento de datos; el tercero introduce al lector en una tarea de minería de datos que centra su aplicación en el análisis de mercadeo; el cuarto está orientado a la predicción de datos, haciendo énfasis en clasificación y regresión; en el quinto muestra una de las tareas más representativas de minería de los datos: la agrupación por datos.
Author: PEREZ LOPEZ, CESAR
Publisher: Ediciones Paraninfo, S.A.
ISBN: 8497324927
Category : Computers
Languages : es
Pages : 804
Get Book Here
Book Description
Se describen los conceptos de minería de datos de la forma más sencilla posible, de modo que sean inteligibles a lectores con formación diversa. Los capítulos comienzan describiendo las técnicas en lenguaje asequible y presentando a continuación la forma de tratarlas mediante aplicaciones prácticas. Una parte importante de cada capítulo son los casos prácticos totalmente resueltos, incluyendo la interpretación de los resultados. Los entornos de trabajo automatizados específicos de minería de datos que se utilizan son SAS Enterprise Miner y SPSS Clementine. Adicionalmente se utilizan determinados procedimientos de SPSS y SAS que realizan tareas de minería de datos de modo sencillo. El libro va acompañado de un CD-ROM que contiene los archivos de datos, tanto de todos los ejemplos que ilustran la parte teórica, como de los ejercicios resueltos.
Author:
Publisher: Editora E-papers
ISBN: 8576502313
Category :
Languages : es
Pages : 219
Get Book Here
Book Description
Author: Antonio Prieto
Publisher: CreateSpace
ISBN: 9781481845847
Category :
Languages : es
Pages : 472
Get Book Here
Book Description
La minería de datos o Data Mining puede definirse inicialmente como un proceso de descubrimiento de nuevas y significativas relaciones, patrones y tendencias al examinar grandes cantidades de datos.La disponibilidad de grandes volúmenes de información y el uso generalizado de herramientas informáticas ha transformado el análisis de datos orientándolo hacia determinadas técnicas especializadas englobadas bajo el nombre de minería de datos o Data Mining.Las técnicas de minería de datos persiguen el descubrimiento automático del conocimiento contenido en la información almacenada de modo ordenado en grandes bases de datos. Estas técnicas tienen como objetivo descubrir patrones, perfiles y tendencias a través del análisis de los datos utilizando técnicas avanzadas como muestreo, análisis exploratorio de datos, técnicas de reducción de la dimensión, técnicas de modelización avanzada, clasificación, segmentación, predicción, reconocimiento de patrones y otras técnicas avanzadas de análisis de datos.Este libro trata la mayoría de estas técnicas desde el punto de vista práctico utilizando el software SAS ENTERPRISE MINER, uno de los más adecuados del mercado para estas tareas.
Author: María Pérez Marqués
Publisher: Alpha Editorial
ISBN: 6076224746
Category : Computers
Languages : es
Pages : 471
Get Book Here
Book Description
Con la ayuda de este libro, a través de ejemplos totalmente resueltos, el lector profundizará en el descubrimiento e interpretación de la información contenida en grandes conjuntos de datos. Se trata de exponer, con sencillez y mediante una metodología interactiva, los conceptos de minería de datos e inteligencia de negocios. Este libro analiza las herramientas más habituales y las posibilidades que ofrecen SAS, SAS Enterprise Guide, SAS Enterprise Miner, IBM SPSS e IBM SPSS Modeler.
Author: Andrea Ahlemeyer-Stubbe
Publisher: John Wiley & Sons
ISBN: 1118763378
Category : Mathematics
Languages : en
Pages : 323
Get Book Here
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: Galit Shmueli
Publisher: John Wiley & Sons
ISBN: 1118729242
Category : Mathematics
Languages : en
Pages : 563
Get Book Here
Book Description
An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition "...full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing."– Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." – ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.
Author: Hugo Santiago Aguirre Mayorga
Publisher: Editorial Pontificia Universidad Javeriana
ISBN: 9587810236
Category : Computers
Languages : es
Pages : 149
Get Book Here
Book Description
Este libro es una propuesta metodológica, sistemática y generalizada en la cual se especifican los pasos que se deben seguir para la aplicación de la minería de procesos, desde la planeación de un proyecto hasta la implantación de sus alternativas de mejora.
Author: Soumen Chakrabarti
Publisher: Morgan Kaufmann
ISBN: 0080877885
Category : Computers
Languages : en
Pages : 477
Get Book Here
Book Description
This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology. The proposed book expertly combines the finest data mining material from the Morgan Kaufmann portfolio. Individual chapters are derived from a select group of MK books authored by the best and brightest in the field. These chapters are combined into one comprehensive volume in a way that allows it to be used as a reference work for those interested in new and developing aspects of data mining. This book represents a quick and efficient way to unite valuable content from leading data mining experts, thereby creating a definitive, one-stop-shopping opportunity for customers to receive the information they would otherwise need to round up from separate sources. Chapters contributed by various recognized experts in the field let the reader remain up to date and fully informed from multiple viewpoints. Presents multiple methods of analysis and algorithmic problem-solving techniques, enhancing the reader’s technical expertise and ability to implement practical solutions. Coverage of both theory and practice brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases.
Author: Meta S. Brown
Publisher: John Wiley & Sons
ISBN: 1118893166
Category : Computers
Languages : en
Pages : 422
Get Book Here
Book Description
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.
