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Digital. Zustand: New. Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS ModelerAbout 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 businessWho This Book Is ForThis 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 predictionsIn DetailIBM 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 approachThis bo.

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Tapa blanda. Zustand: Nuevo. IBM SPSS Modeler es una herramienta integrada de minería de datos (Data Mining), Business Intelligence (BI) y Big Data. Permite trabajar con diversas fuentes de orígenes de datos (ASCII, XLS, ODBC, etc.), presenta una interfaz visual basada en procesos/flujos de datos (streams) e incorpora una amplia variedad de herramientas de minería de datos e inteligencia de negocios (exploración, correlación, reglas de asociación, regresión, segmentación, clasificación, redes neuronales, reglas y árboles de decisión, patrones, etc.), manipulación de datos (pick & mix, muestreo, matching y separación, etc.), combinación de modelos, visualización de datos, exportación de modelos a distintos lenguajes (C, SPSS, SAS, etc.), exportación de datos integrada a otros programas y generación de informes. Todas estas herramientas se estudian a lo largo del libro y se ilustran con ejemplos. El entorno de IBM SPSS Modeler está basado en nodos que se van disponiendo y conectando para formar un flujo, o stream, traducido también como ruta . Los streams pueden almacenarse en ficheros separados o en proyectos que engloban a varios de ellos que se puede cargar, guardar, modificar, reejecutar o reorganizar y que son independientes de las fuentes de datos. Estas características permiten automatizar los procesos de inteligencia de negocios. A lo largo del libro se desarrollan totalmente más de un centenar de ejemplos de minería de datos con la plataforma IBM SPSS Modeler. También se incorporan notas.

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Zustand: New. IBM SPSS Modeler allows quick, efficient predictive analytics and insight building from your data, and is a popularly used data mining tool. This book will guide you through the data mining process, and presents relevant statistical methods which are used t.

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Digital. Zustand: New. Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS ModelerAbout 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 businessWho This Book Is ForThis 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 predictionsIn DetailIBM 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 approachThis bo.

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Zustand: New. &Uumlber den AutorrnrnKeith McCormick Keith McCormick is an independent data miner, trainer, conference speaker, and author. He has been using statistics software tools since the early 90s, and has been conducting training since 1997. He has be.