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 IBM SPSS Modeler Cookbook written by Keith McCormick and published by Packt Publishing Ltd. This book was released on 2013-10-23 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a practical cookbook with intermediate-advanced recipes for SPSS Modeler data analysts. It is loaded with step-by-step examples explaining the process followed by the experts.If you have had some hands-on experience with IBM SPSS Modeler and now want to go deeper and take more control over your data mining process, this is the guide for you. It is ideal for practitioners who want to break into advanced analytics.
Download or read book IBM Spss Modeler written by Business Books and published by CreateSpace. This book was released on 2015-09-29 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: IBM SPSS Modeler is a set of data mining tools that enable you to quickly develop predictive models using business expertise and deploy them into business operations to improve decision making. Designed around the industry-standard CRISP-DM model, IBM SPSS Modeler supports the entire data mining process, from data to better business results. IBM SPSS Modeler offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics. The methods available on the Modeling palette allow you to derive new information from your data and to develop predictive models. Each method has certain strengths and is best suited for particular types of problems. SPSS Modeler can be purchased as a standalone product, or used as a client in combination with SPSS Modeler Server. A number of additional options are also available, as summarized in the following sections. SPSS Modeler is a functionally complete version of the product that you install and run on your personal computer. You can run SPSS Modeler in local mode as a standalone product, or use it in distributed mode along with IBM SPSS Modeler Server for improved performance on large data sets. With SPSS Modeler, you can build accurate predictive models quickly and intuitively, without programming. Using the unique visual interface, you can easily visualize the data mining process. With the support of the advanced analytics embedded in the product, you can discover previously hidden patterns and trends in your data. You can model outcomes and understand the factors that influence them, enabling you to take advantage of business opportunities and mitigate risks.
Download or read book Data Mining with SPSS Modeler written by Tilo Wendler and published by Springer. This book was released on 2021-05-25 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods. Focusing on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs, it also features a variety of exercises and solutions, as well as an accompanying website with data sets and SPSS Modeler streams. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice. This revised and updated second edition includes a new chapter on imbalanced data and resampling techniques as well as an extensive case study on the cross-industry standard process for data mining.
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 IBM SPSS Modeler Essentials written by Keith McCormick and published by Packt Publishing Ltd. This book was released on 2017-12-26 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler About This Book Get up–and-running with IBM SPSS Modeler without going into too much depth. Identify interesting relationships within your data and build effective data mining and predictive analytics solutions A quick, easy–to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business Who This Book Is For This book is ideal for those who are new to SPSS Modeler and want to start using it as quickly as possible, without going into too much detail. An understanding of basic data mining concepts will be helpful, to get the best out of the book. What You Will Learn Understand the basics of data mining and familiarize yourself with Modeler's visual programming interface Import data into Modeler and learn how to properly declare metadata Obtain summary statistics and audit the quality of your data Prepare data for modeling by selecting and sorting cases, identifying and removing duplicates, combining data files, and modifying and creating fields Assess simple relationships using various statistical and graphing techniques Get an overview of the different types of models available in Modeler Build a decision tree model and assess its results Score new data and export predictions In Detail IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler's easy to learn “visual programming” style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model's performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models. Style and approach This book empowers users to build practical & accurate predictive models quickly and intuitively. With the support of the advanced analytics users can discover hidden patterns and trends.This will help users to understand the factors that influence them, enabling you to take advantage of business opportunities and mitigate risks.
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 Using SAS Enterprise Miner written by Randall Matignon and published by John Wiley & Sons. This book was released on 2007-08-03 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner. The Sample, Explore, Modify, Model, and Assess (SEMMA) methodology of SAS Enterprise Miner is an extremely valuable analytical tool for making critical business and marketing decisions. Until now, there has been no single, authoritative book that explores every node relationship and pattern that is a part of the Enterprise Miner software with regard to SEMMA design and data mining analysis. Data Mining Using SAS Enterprise Miner introduces readers to a wide variety of data mining techniques and explains the purpose of-and reasoning behind-every node that is a part of the Enterprise Miner software. Each chapter begins with a short introduction to the assortment of statistics that is generated from the various nodes in SAS Enterprise Miner v4.3, followed by detailed explanations of configuration settings that are located within each node. Features of the book include: The exploration of node relationships and patterns using data from an assortment of computations, charts, and graphs commonly used in SAS procedures A step-by-step approach to each node discussion, along with an assortment of illustrations that acquaint the reader with the SAS Enterprise Miner working environment Descriptive detail of the powerful Score node and associated SAS code, which showcases the important of managing, editing, executing, and creating custom-designed Score code for the benefit of fair and comprehensive business decision-making Complete coverage of the wide variety of statistical techniques that can be performed using the SEMMA nodes An accompanying Web site that provides downloadable Score code, training code, and data sets for further implementation, manipulation, and interpretation as well as SAS/IML software programming code This book is a well-crafted study guide on the various methods employed to randomly sample, partition, graph, transform, filter, impute, replace, cluster, and process data as well as interactively group and iteratively process data while performing a wide variety of modeling techniques within the process flow of the SAS Enterprise Miner software. Data Mining Using SAS Enterprise Miner is suitable as a supplemental text for advanced undergraduate and graduate students of statistics and computer science and is also an invaluable, all-encompassing guide to data mining for novice statisticians and experts alike.
Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Ken Yale and published by Elsevier. This book was released on 2017-11-09 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Download or read book Data Mining with SPSS Modeler written by Tilo Wendler and published by Springer Nature. This book was released on 2021-05-24 with total page 1285 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this textbook introduces readers to the IBM SPSS Modeler and guides them through data mining processes and relevant statistical methods. Focusing on step-by-step tutorials and well-documented examples that help demystify complex mathematical algorithms and computer programs, it also features a variety of exercises and solutions, as well as an accompanying website with data sets and SPSS Modeler streams. While intended for students, the simplicity of the Modeler makes the book useful for anyone wishing to learn about basic and more advanced data mining, and put this knowledge into practice. This revised and updated second edition includes a new chapter on imbalanced data and resampling techniques as well as an extensive case study on the cross-industry standard process for data mining.
Download or read book Data Mining written by Robert Groth and published by Prentice Hall. This book was released on 2000 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: PLEASE PROVIDE COURSE INFORMATION PLEASE PROVIDE
Download or read book Enabling Real time Analytics on IBM z Systems Platform written by Lydia Parziale and published by IBM Redbooks. This book was released on 2016-08-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Regarding online transaction processing (OLTP) workloads, IBM® z SystemsTM platform, with IBM DB2®, data sharing, Workload Manager (WLM), geoplex, and other high-end features, is the widely acknowledged leader. Most customers now integrate business analytics with OLTP by running, for example, scoring functions from transactional context for real-time analytics or by applying machine-learning algorithms on enterprise data that is kept on the mainframe. As a result, IBM adds investment so clients can keep the complete lifecycle for data analysis, modeling, and scoring on z Systems control in a cost-efficient way, keeping the qualities of services in availability, security, reliability that z Systems solutions offer. Because of the changed architecture and tighter integration, IBM has shown, in a customer proof-of-concept, that a particular client was able to achieve an orders-of-magnitude improvement in performance, allowing that client's data scientist to investigate the data in a more interactive process. Open technologies, such as Predictive Model Markup Language (PMML) can help customers update single components instead of being forced to replace everything at once. As a result, you have the possibility to combine your preferred tool for model generation (such as SAS Enterprise Miner or IBM SPSS® Modeler) with a different technology for model scoring (such as Zementis, a company focused on PMML scoring). IBM SPSS Modeler is a leading data mining workbench that can apply various algorithms in data preparation, cleansing, statistics, visualization, machine learning, and predictive analytics. It has over 20 years of experience and continued development, and is integrated with z Systems. With IBM DB2 Analytics Accelerator 5.1 and SPSS Modeler 17.1, the possibility exists to do the complete predictive model creation including data transformation within DB2 Analytics Accelerator. So, instead of moving the data to a distributed environment, algorithms can be pushed to the data, using cost-efficient DB2 Accelerator for the required resource-intensive operations. This IBM Redbooks® publication explains the overall z Systems architecture, how the components can be installed and customized, how the new IBM DB2 Analytics Accelerator loader can help efficient data loading for z Systems data and external data, how in-database transformation, in-database modeling, and in-transactional real-time scoring can be used, and what other related technologies are available. This book is intended for technical specialists and architects, and data scientists who want to use the technology on the z Systems platform. Most of the technologies described in this book require IBM DB2 for z/OS®. For acceleration of the data investigation, data transformation, and data modeling process, DB2 Analytics Accelerator is required. Most value can be achieved if most of the data already resides on z Systems platforms, although adding external data (like from social sources) poses no problem at all.
Download or read book Data Mining Techniques in CRM written by Konstantinos K. Tsiptsis and published by John Wiley & Sons. This book was released on 2011-08-24 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.
Download or read book Data Mining with Rattle and R written by Graham Williams and published by Springer Science & Business Media. This book was released on 2011-08-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.
Download or read book Integration of Data Mining in Business Intelligence Systems written by Azevedo, Ana and published by IGI Global. This book was released on 2014-09-30 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.
Download or read book Data Mining For Dummies written by Meta S. Brown and published by John Wiley & Sons. This book was released on 2014-09-04 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.
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"
