Download or read book Data Mining Con Herramientas de IBM IBM SPSS Modeler written by and published by . This book was released on 2015-12-27 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: La finalidad del Big Data, Data Mining y todas las tecnologias asociadas (Analytics), es convertir los datos en informacion util para la toma de decisiones en cualquier organizacion. Se trata de conseguir un acercamiento proactivo al cliente mediante entornos analiticos que sean fiables y escalables, y permitan crear nuevos productos, modelos de negocio, etc. Y todo esto conlleva la adaptacion de procesos y tecnologias porque hay que analizar los datos de una manera diferente. Este libro presenta las tecnicas de Data Mining desde la perespectiva de las herramiemtas de IBM, en concreto IBM SPSS MODELER"

Download or read book Data Mining with IBM SPSS Modeler IBM SPSS Clementine written by César Pérez and published by Createspace Independent Pub. This book was released on 2013-06-14 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most common techniques used in data mining in a simple and easy to understand through one of the most common software solutions from among those existing in the market, in particular, IBM SPSS CLEMENTINE whose current name is IBM SPSS MODELER. Pursued as initial aim clarifying the applications concerning methods traditionally rated as difficult or dull. It seeks to present applications in data mining without having to manage high mathematical developments or complicated theoretical algorithms, which is the most common reason for the difficulties in understanding and implementation of this matter. Today data mining is used in different fields of science. Noteworthy applications in banking, and financial analysis of markets and trade, insurance and private health, in education, in industrial processes, in medicine, biology and bioengineering, telecommunications and in many other areas. Essentials to get started in data mining, regardless of the field in which it is applied, is the understanding of own concepts, task that does not require nor much less the domain of scientific apparatus involved in the matter. Later, when either necessary operative advanced, computer programs allow the results without having to decipher the mathematical development of the algorithms that are under the procedures. This book describes the simplest possible data mining concepts, so that they are understandable by readers with different training. The chapters begin describing the techniques in affordable language and then presenting the way to treat them through practical applications. An important part of each chapter are case studies completely resolved, including the interpretation of the results, which is precisely the most important thing in any matter with which they work. The book begins with an introduction to mining data and its phases. In successive chapters develop the initial phases (selection of information, data exploration, data cleansing, transformation of data, etc.). Subsequently elaborates on specific data mining, both predictive and descriptive techniques. Predictive techniques covers all models of regression, discriminant analysis, decision trees, neural networks and other techniques based on models. The descriptive techniques vary dimension reduction techniques, techniques of classification and segmentation (clustering), and exploratory data analysis techniques.

Download or read book DATA MINING con IBM SPSS MODELER IBM SPSS CLEMENTINE written by Antonio Prieto and published by Createspace Independent Pub. This book was released on 2012-12-26 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 IBM SPSS MODELER (IBM SPSS CLEMENTINE), uno de los más adecuados del mercado para estas tareas.

Download or read book Big Data y Data Mining written by Cesar Perez Lopez and published by Createspace Independent Publishing Platform. This book was released on 2017-10-16 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: El an�lisis de datos de hoy en d�a requiere el uso de t�cnicas estad�sticas para aprender de los datos, de patrones de relieve y anomal�as, de predicciones y de profesionales que sepan utilizarlas. El empleo de tecnolog�as Big Data no solo permite aumentar la capacidad de procesamiento, tambi�n se trata de encontrar esas ideas que nos permitan obtener el conocimiento embebido en los datos, siempre y cuando se disponga de los perfiles y experiencia para llevarlo a cabo. Por esta raz�n, las t�cnicas de Analytics (esencialmente Data Mining y Bussines Intelligence) y el Big Data caminan juntos para la explotaci�n �ptima de la informaci�n. Profesionales, con habilidades en matem�ticas, estad�sticas e ingenier�a inform�tica, que son capaces de extraer el m�ximo valor de los datos de la organizaci�n mediante Analytics, deben de trabajar juntos con las infraestructuras �ptimas de Big Data. La gesti�n y an�lisis de los grandes datos, estructurados y no estructurados, aplicados en campos como la investigaci�n cient�fica, sanidad, seguridad, redes sociales o medios de comunicaci�n, entre otros, constituye para las empresas una herramienta �nica de ganar competitividad y de mejora de la vida ciudadana. Esta herramienta s�lo se optimiza con la aplicaci�n conjunta de t�cnicas de Analytics y Big Data.Este libro desarrolla aplicaciones de Big Data y Data Mining utilizando herramientas de IBM, como son: Power Systems e IBM SPSS Modeler.

Download or read book DATA MINING The CRISP DM METHODOLOGY The CLEM Language and IBM SPSS MODELER written by Perez Lopez Cesar Perez Lopez and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book T cnicas de miner a de datos e inteligencia de negocios IBM SPSS Modeler written by César Pérez López and published by . This book was released on 2014 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Mining with IBM SPSS Through Examples written by Cesar Lopez and published by CreateSpace. This book was released on 2013-06-26 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most common techniques used in data mining in a simple and easy to understand through one of the most common software solutions from among those existing in the market, in particular, IBM SPSS. Pursued as initial aim clarifying the applications concerning methods traditionally rated as difficult or dull. It seeks to present applications in data mining without having to manage high mathematical developments or complicated theoretical algorithms, which is the most common reason for the difficulties in understanding and implementation of this matter. Today data mining is used in different fields of science. Noteworthy applications in banking, and financial analysis of markets and trade, insurance and private health, in education, in industrial processes, in medicine, biology and bioengineering, telecommunications and in many other areas. Essentials to get started in data mining, regardless of the field in which it is applied, is the understanding of own concepts, task that does not require nor much less the domain of scientific apparatus involved in the matter. Later, when either necessary operative advanced, computer programs allow the results without having to decipher the mathematical development of the algorithms that are under the procedures. This book describes the simplest possible data mining concepts, so that they are understandable by readers with different training. The chapters begin describing the techniques in affordable language and then presenting the way to treat them through practical applications. An important part of each chapter are case studies completely resolved, including the interpretation of the results, which is precisely the most important thing in any matter with which they work. The book begins with an introduction to mining data and its phases. In successive chapters develop the initial phases (selection of information, data exploration, data cleansing, transformation of data, etc.). Subsequently elaborates on specific data mining, both predictive and descriptive techniques. Predictive techniques covers all models of regression, discriminant analysis, decision trees, neural networks and other techniques based on models. The descriptive techniques vary dimension reduction techniques, techniques of classification and segmentation (clustering), and exploratory data analysis techniques.

Download or read book DATA MINING con IBM SPSS a Traves de Ejemplos written by Antonio Prieto and published by Createspace Independent Pub. This book was released on 2012-12-26 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 IBM SPSS, uno de los más adecuados del mercado para estas tareas.

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2016-04-18 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Big Data Aplicado E Inteligencia de Negocios Con Herramientas de Software written by F Marqués and published by Independently Published. This book was released on 2022-09-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: El libro comienza analizando herramientas de computación masiva en los ecosistemas de Big Data con especial atención a Hadoop, Mapreduce, Hadoop Distribute File System y Hadoop Common Components (Pig, Hive, Flume, Oozie, Hbase, Sqoop, Mahout y otras). A continuación se aborda la automatización de trabajos y se presentan ejemplos desarrollados con SQL Server. También se presenta el ecosistema Hadoop de Apache Ambari. Adicionalmente se presentan las herramientas de Big Data Analytics de SAS (SAS Access Interface to Hadoop, SAS Data Management, SAS Visual Analytics, SAS Visual Statistics, SAS In Memory Statistics for Hadoop, SAS High Performance Data Mining, SAS High Performance Text Mining, SAS VIYA, etc.) También se presentan las herramientas de Big Data Analytics de Oracle (Big Data Appliance, Big Data Connectors, NoSQL Database, Exadata, Business Analytics, etc.), Microsoft (HDInsight, Azure, etc.) e IBM (IBM Solution for Hadoop Power Systems Edition, BM AIX Solution Editions para Cognos y SPSS, IBM SPSS Modeler, etc.). A continuación se abordan la calidad e integridad de los datos en procesos de Big Data y el movimiento de datos entre clústers. Como ejemplo se desarrolla la copia y movimiento de bases de datos entre servidores en SQL Server. Más adelante se tratan las herramientas de monitorización de clústers HYPER-V, Hadoop y Ganglia, así como herramientas para interfaz web y otras. Finalmente se profundiza en las técnicas de Big Data e Inteligencia de Negocios. Se analizan las herramientas más importantes de Business Intelligence (Business Objects, MicroStrategy, Tableau, Power BI, Qlik, Domo, Pentaho, etc.) con especial atención a los cuadros de mando. Se describen las herramientas SAS Visual Analytics y herramientas de SAP para cuadros de mando. Por último, se describe la implementación del KDD (Knowledge Discovery in Data Bases) con herramientas de SAS (SAS Enterprise Miner) e IBM (IBM SPSS Modeler) a través de ejemplos.

Download or read book Modelos Con Herramientas de Mineria de Datos Ejercicios Con Modeler y SAS Miner written by Cesar Lopez and published by CreateSpace. This book was released on 2013-07-09 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: La disponibilidad de grandes volúmenes de datos y el uso generalizado de herramientas informáticas ha transformado la econometría y el análisis multivariante de datos orientándolo hacia determinadas técnicas especializadas englobadas bajo el nombre de minería de datos o Data Mining. La minería de datos puede definirse como un proceso de descubrimiento de nuevas y significativas relaciones, patrones y tendencias al examinar grandes cantidades de datos. 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 relaciones, patrones, perfiles y tendencias a través del análisis de los datos utilizando técnicas avanzadas de modelización econométrica y de análisis de datos.En este libro se tratan los modelos econométricos a través de técnicas de minería de datos, tanto predictivas como de clasificación. Todo el desarrollo de ejercicios prácticos se realiza desde una óptica multisoftware, utilizándose el software más actual del mercado adecuado para estas tareas econométricas no triviales. En concreto se resuelven los ejercicios con IBM SPSS MODELER Y SAS ENTERPRISE MINER.

Download or read book Modelos Predictivos Redes Neuronales y Tecnicas de Segmentacion Con Ibm Spss Modeler written by Csar Lpez Prez and published by Createspace Independent Publishing Platform. This book was released on 2016-04-19 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: La clasificación de las técnicas de análisis de datos discrimina entre la existencia o no de variables explicativas y explicadas. Si existe una dependencia entre las variables explicadas y sus correspondientes variables explicativas, que pueda plasmarse en un modelo, estamos ante las técnicas predictivas o métodos explicativos o técnicas de modelado predictivo, herramientas fundamentales en Inteligencia de Negocios y Minería de Datos. Este tipo de técnicas de análisis de la dependencia pueden clasificarse en función de la naturaleza métrica o no métrica de las variables independientes y dependientes dando lugar a los diferentes tipos de modelos tratados en este libro, como son los modelos lineales generales, modelos de redes neuronales, árboles de decisión, modelos logísticos, modelos de análisis discriminante, modelos de series temporales, modelos de clasificación y segmentación automáticos y otros tipos de modelos utilizados en Data Mining y Business Intelligence.

Download or read book Artificial Intelligence written by Sandeep Reddy and published by CRC Press. This book was released on 2020-12-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.

Download or read book Sistemas De Big Data written by and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Mining Methods and Models written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2006-02-02 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information * The insight into how the data mining algorithms actually work * The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a "white box" methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, "Modeling Response to Direct-Mail Marketing" * Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises * Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software * Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.

Download or read book Discovering Data Mining written by Peter Cabena and published by . This book was released on 1998 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through extensive case studies and examples, this book provides practical guidance on all aspects of implementing data mining: technical, business, and social. The book also demonstrates IBM's powerful new intelligent Miner tool and shows how it can be applied.

Download or read book Data Mining Methods and Models Set written by Daniel T. Larose and published by Wiley-Interscience. This book was released on 2007-06-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Apply powerful Data Mining Methods and Models to Leverage your Data for Actionable Results Data Mining Methods and Models provides: * The latest techniques for uncovering hidden nuggets of information* The insight into how the data mining algorithms actually work* The hands-on experience of performing data mining on large data sets Data Mining Methods and Models: * Applies a white box methodology, emphasizing an understanding of the model structures underlying the softwareWalks the reader through the various algorithms and provides examples of the operation of the algorithms on actual large data sets, including a detailed case study, Modeling Response to Direct-Mail Marketing* Tests the reader's level of understanding of the concepts and methodologies, with over 110 chapter exercises* Demonstrates the Clementine data mining software suite, WEKA open source data mining software, SPSS statistical software, and Minitab statistical software* Includes a companion Web site, www.dataminingconsultant.com, where the data sets used in the book may be downloaded, along with a comprehensive set of data mining resources. Faculty adopters of the book have access to an array of helpful resources, including solutions to all exercises, a PowerPoint(r) presentation of each chapter, sample data mining course projects and accompanying data sets, and multiple-choice chapter quizzes. With its emphasis on learning by doing, this is an excellent textbook for students in business, computer science, and statistics, as well as a problem-solving reference for data analysts and professionals in the field. An Instructor's Manual presenting detailed solutions to all the problems in the book is available onlne.