Decision Trees For Analytics Using Sas Enterprise Miner

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Decision Trees for Analytics Using SAS Enterprise Miner

Author : Barry De Ville
Publisher :
ISBN 13 : 9781642953138
Total Pages : 268 pages
Book Rating : 4.9/5 (531 download)

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Book Synopsis Decision Trees for Analytics Using SAS Enterprise Miner by : Barry De Ville

Download or read book Decision Trees for Analytics Using SAS Enterprise Miner written by Barry De Ville and published by . This book was released on 2019-07-03 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision Trees for Analytics Using SAS Enterprise Miner is the most comprehensive treatment of decision tree theory, use, and applications available in one easy-to-access place. This book illustrates the application and operation of decision trees in business intelligence, data mining, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements data mining approaches such as regression, as well as other business intelligence applications that incorporate tabular reports, OLAP, or multidimensional cubes. An expanded and enhanced release of Decision Trees for Business Intelligence and Data Mining Using SAS Enterprise Miner, this book adds up-to-date treatments of boosting and high-performance forest approaches and rule induction. There is a dedicated section on the most recent findings related to bias reduction in variable selection. It provides an exhaustive treatment of the end-to-end process of decision tree construction and the respective considerations and algorithms, and it includes discussions of key issues in decision tree practice. Analysts who have an introductory understanding of data mining and who are looking for a more advanced, in-depth look at the theory and methods of a decision tree approach to business intelligence and data mining will benefit from this book.

Decision Trees for Business Intelligence and Data Mining

Author : Barry De Ville
Publisher : SAS Press
ISBN 13 : 9781590475676
Total Pages : 224 pages
Book Rating : 4.4/5 (756 download)

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Book Synopsis Decision Trees for Business Intelligence and Data Mining by : Barry De Ville

Download or read book Decision Trees for Business Intelligence and Data Mining written by Barry De Ville and published by SAS Press. This book was released on 2006 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: This example-driven guide illustrates the application and operation of decision trees in data mining, business intelligence, business analytics, prediction, and knowledge discovery. It explains in detail the use of decision trees as a data mining technique and how this technique complements and supplements other business intelligence applications.

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Author : Olivia Parr-Rud
Publisher : SAS Institute
ISBN 13 : 1629593273
Total Pages : 182 pages
Book Rating : 4.6/5 (295 download)

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Book Synopsis Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner by : Olivia Parr-Rud

Download or read book Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner written by Olivia Parr-Rud and published by SAS Institute. This book was released on 2014-10 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. --

Predictive Modeling with SAS Enterprise Miner

Author : Kattamuri S. Sarma
Publisher : SAS Institute
ISBN 13 : 163526040X
Total Pages : 574 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis Predictive Modeling with SAS Enterprise Miner by : Kattamuri S. Sarma

Download or read book Predictive Modeling with SAS Enterprise Miner written by Kattamuri S. Sarma and published by SAS Institute. This book was released on 2017-07-20 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: « Written for business analysts, data scientists, statisticians, students, predictive modelers, and data miners, this comprehensive text provides examples that will strengthen your understanding of the essential concepts and methods of predictive modeling. »--

Applying Predictive Analytics

Author : Richard V. McCarthy
Publisher : Springer
ISBN 13 : 3030140385
Total Pages : 205 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Applying Predictive Analytics by : Richard V. McCarthy

Download or read book Applying Predictive Analytics written by Richard V. McCarthy and published by Springer. This book was released on 2019-03-12 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be utilized and explained within the context of enhancing business opportunities. Each chapter includes an opening vignette that provides real-life example of how business analytics have been used in various aspects of organizations to solve issue or improve their results. A running case provides an example of a how to build and analyze a complex analytics model and utilize it to predict future outcomes.

Applied Data Mining for Forecasting Using SAS

Author : Tim Rey
Publisher : SAS Institute
ISBN 13 : 1612900933
Total Pages : 336 pages
Book Rating : 4.6/5 (129 download)

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Book Synopsis Applied Data Mining for Forecasting Using SAS by : Tim Rey

Download or read book Applied Data Mining for Forecasting Using SAS written by Tim Rey and published by SAS Institute. This book was released on 2012-07-02 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Data Mining for Forecasting Using SAS, by Tim Rey, Arthur Kordon, and Chip Wells, introduces and describes approaches for mining large time series data sets. Written for forecasting practitioners, engineers, statisticians, and economists, the book details how to select useful candidate input variables for time series regression models in environments when the number of candidates is large, and identifies the correlation structure between selected candidate inputs and the forecast variable. This book is essential for forecasting practitioners who need to understand the practical issues involved in applied forecasting in a business setting. Through numerous real-world examples, the authors demonstrate how to effectively use SAS software to meet their industrial forecasting needs. This book is part of the SAS Press program.

Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition

Author : Randall S. Collica
Publisher : SAS Institute
ISBN 13 : 1629605298
Total Pages : 356 pages
Book Rating : 4.6/5 (296 download)

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Book Synopsis Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition by : Randall S. Collica

Download or read book Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition written by Randall S. Collica and published by SAS Institute. This book was released on 2017-03-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: A working guide that uses real-world data, this step-by-step resource will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. --

SAS Enterprise Miner Exercise and Assignment Book

Author : Varol Onur Kayhan
Publisher : Varol Onur Kayhan
ISBN 13 :
Total Pages : 128 pages
Book Rating : 4./5 ( download)

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Book Synopsis SAS Enterprise Miner Exercise and Assignment Book by : Varol Onur Kayhan

Download or read book SAS Enterprise Miner Exercise and Assignment Book written by Varol Onur Kayhan and published by Varol Onur Kayhan. This book was released on 2020-04-07 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written for students in higher education. Instructors teaching predictive analytics courses can assign this book to their students to expose them to predictive analytics techniques using SAS Enterprise Miner. The book is developed using SAS Enterprise Miner 14.3, but it should apply to other versions with little to no changes. This book does not require students to have any previous knowledge of SAS Enterprise Miner. It walks students through the predictive analytics process using step-by-step by instructions. Even though the contents of this book can be completed by anyone who has access to SAS Enterprise Miner, knowledge of predictive analytics concepts is essential. Also, this book is not a substitute for any lecture or textbook. It is best if this book is used in parallel to lectures.

Handbook of Statistical Analysis and Data Mining Applications

Author : Robert Nisbet
Publisher : Elsevier
ISBN 13 : 0124166458
Total Pages : 822 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Handbook of Statistical Analysis and Data Mining Applications by : Robert Nisbet

Download or read book Handbook of Statistical Analysis and Data Mining Applications written by Robert Nisbet and published by Elsevier. This book was released on 2017-11-09 with total page 822 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

Decision Trees With SAS Enterprise Miner

Author : Scientific Books
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781523218158
Total Pages : 196 pages
Book Rating : 4.2/5 (181 download)

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Book Synopsis Decision Trees With SAS Enterprise Miner by : Scientific Books

Download or read book Decision Trees With SAS Enterprise Miner written by Scientific Books and published by Createspace Independent Publishing Platform. This book was released on 2016-01-02 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models to predict a continuous target. Some examples are presented. One example shows how to build a decision tree model to predict response to direct mail. In this example, the target variable is binary, taking on the values response and no response. Other example shows how to build a regression tree model to forecast a continuous (but interval-scaled) target often used in the auto insurance industry, namely loss frequency . Loss frequency can also be modeled as a categorical target variable if it takes on only a few values but in this example it is treated as a continuous target. Successive chapters present examples that clarify the application of the tree models. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used.

Machine Learning with SAS Viya

Author : SAS Institute Inc.
Publisher : SAS Institute
ISBN 13 : 1951685377
Total Pages : 295 pages
Book Rating : 4.9/5 (516 download)

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Book Synopsis Machine Learning with SAS Viya by : SAS Institute Inc.

Download or read book Machine Learning with SAS Viya written by SAS Institute Inc. and published by SAS Institute. This book was released on 2020-05-29 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master machine learning with SAS Viya! Machine learning can feel intimidating for new practitioners. Machine Learning with SAS Viya provides everything you need to know to get started with machine learning in SAS Viya, including decision trees, neural networks, and support vector machines. The analytics life cycle is covered from data preparation and discovery to deployment. Working with open-source code? Machine Learning with SAS Viya has you covered – step-by-step instructions are given on how to use SAS Model Manager tools with open source. SAS Model Studio features are highlighted to show how to carry out machine learning in SAS Viya. Demonstrations, practice tasks, and quizzes are included to help sharpen your skills. In this book, you will learn about: Supervised and unsupervised machine learning Data preparation and dealing with missing and unstructured data Model building and selection Improving and optimizing models Model deployment and monitoring performance

End-to-End Data Science with SAS

Author : James Gearheart
Publisher : SAS Institute
ISBN 13 : 1642958069
Total Pages : 246 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis End-to-End Data Science with SAS by : James Gearheart

Download or read book End-to-End Data Science with SAS written by James Gearheart and published by SAS Institute. This book was released on 2020-06-26 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn data science concepts with real-world examples in SAS! End-to-End Data Science with SAS: A Hands-On Programming Guide provides clear and practical explanations of the data science environment, machine learning techniques, and the SAS programming knowledge necessary to develop machine learning models in any industry. The book covers concepts including understanding the business need, creating a modeling data set, linear regression, parametric classification models, and non-parametric classification models. Real-world business examples and example code are used to demonstrate each process step-by-step. Although a significant amount of background information and supporting mathematics are presented, the book is not structured as a textbook, but rather it is a user’s guide for the application of data science and machine learning in a business environment. Readers will learn how to think like a data scientist, wrangle messy data, choose a model, and evaluate the model’s effectiveness. New data scientists or professionals who want more experience with SAS will find this book to be an invaluable reference. Take your data science career to the next level by mastering SAS programming for machine learning models.

Cluster Analysis and Decision Trees with SAS Enterprise Miner

Author : Scientific Books
Publisher : CreateSpace
ISBN 13 : 9781514654477
Total Pages : 178 pages
Book Rating : 4.6/5 (544 download)

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Book Synopsis Cluster Analysis and Decision Trees with SAS Enterprise Miner by : Scientific Books

Download or read book Cluster Analysis and Decision Trees with SAS Enterprise Miner written by Scientific Books and published by CreateSpace. This book was released on 2015-06-22 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused in Cluster Analysis and Decision Trees. SAS Institute defines the concept of Data Mining as the process of selecting (Selecting), explore (Exploring), modify (Modifying), modeling (Modeling) and rating (Assessment) large amounts of data with the aim of uncovering unknown patterns which can be used as a comparative advantage with respect to competitors. This process is summarized with the acronym SEMMA which are the initials of the 5 phases which comprise the process of Data Mining according to SAS Institute."

Data Mining with Rattle and R

Author : Graham Williams
Publisher : Springer Science & Business Media
ISBN 13 : 144199890X
Total Pages : 382 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Data Mining with Rattle and R by : Graham Williams

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.

The Analytics Lifecycle Toolkit

Author : Gregory S. Nelson
Publisher : John Wiley & Sons
ISBN 13 : 1119425093
Total Pages : 464 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis The Analytics Lifecycle Toolkit by : Gregory S. Nelson

Download or read book The Analytics Lifecycle Toolkit written by Gregory S. Nelson and published by John Wiley & Sons. This book was released on 2018-03-07 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: An evidence-based organizational framework for exceptional analytics team results The Analytics Lifecycle Toolkit provides managers with a practical manual for integrating data management and analytic technologies into their organization. Author Gregory Nelson has encountered hundreds of unique perspectives on analytics optimization from across industries; over the years, successful strategies have proven to share certain practices, skillsets, expertise, and structural traits. In this book, he details the concepts, people and processes that contribute to exemplary results, and shares an organizational framework for analytics team functions and roles. By merging analytic culture with data and technology strategies, this framework creates understanding for analytics leaders and a toolbox for practitioners. Focused on team effectiveness and the design thinking surrounding product creation, the framework is illustrated by real-world case studies to show how effective analytics team leadership works on the ground. Tools and templates include best practices for process improvement, workforce enablement, and leadership support, while guidance includes both conceptual discussion of the analytics life cycle and detailed process descriptions. Readers will be equipped to: Master fundamental concepts and practices of the analytics life cycle Understand the knowledge domains and best practices for each stage Delve into the details of analytical team processes and process optimization Utilize a robust toolkit designed to support analytic team effectiveness The analytics life cycle includes a diverse set of considerations involving the people, processes, culture, data, and technology, and managers needing stellar analytics performance must understand their unique role in the process of winnowing the big picture down to meaningful action. The Analytics Lifecycle Toolkit provides expert perspective and much-needed insight to managers, while providing practitioners with a new set of tools for optimizing results.

Predictive Analytics and Data Mining

Author : Vijay Kotu
Publisher : Morgan Kaufmann
ISBN 13 : 0128016507
Total Pages : 447 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis Predictive Analytics and Data Mining by : Vijay Kotu

Download or read book Predictive Analytics and Data Mining written by Vijay Kotu and published by Morgan Kaufmann. This book was released on 2014-11-27 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Put Predictive Analytics into ActionLearn the basics of Predictive Analysis and Data Mining through an easy to understand conceptual framework and immediately practice the concepts learned using the open source RapidMiner tool. Whether you are brand new to Data Mining or working on your tenth project, this book will show you how to analyze data, uncover hidden patterns and relationships to aid important decisions and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its operations. This book is ideal for business users, data analysts, business analysts, business intelligence and data warehousing professionals and for anyone who wants to learn Data Mining.You’ll be able to:1. Gain the necessary knowledge of different data mining techniques, so that you can select the right technique for a given data problem and create a general purpose analytics process.2. Get up and running fast with more than two dozen commonly used powerful algorithms for predictive analytics using practical use cases.3. Implement a simple step-by-step process for predicting an outcome or discovering hidden relationships from the data using RapidMiner, an open source GUI based data mining tool Predictive analytics and Data Mining techniques covered: Exploratory Data Analysis, Visualization, Decision trees, Rule induction, k-Nearest Neighbors, Naïve Bayesian, Artificial Neural Networks, Support Vector machines, Ensemble models, Bagging, Boosting, Random Forests, Linear regression, Logistic regression, Association analysis using Apriori and FP Growth, K-Means clustering, Density based clustering, Self Organizing Maps, Text Mining, Time series forecasting, Anomaly detection and Feature selection. Implementation files can be downloaded from the book companion site at www.LearnPredictiveAnalytics.com Demystifies data mining concepts with easy to understand language Shows how to get up and running fast with 20 commonly used powerful techniques for predictive analysis Explains the process of using open source RapidMiner tools Discusses a simple 5 step process for implementing algorithms that can be used for performing predictive analytics Includes practical use cases and examples

Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT

Author : Iain Brown
Publisher :
ISBN 13 : 9781642953152
Total Pages : 174 pages
Book Rating : 4.9/5 (531 download)

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Book Synopsis Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT by : Iain Brown

Download or read book Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT written by Iain Brown and published by . This book was released on 2019-07-03 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combine complex concepts facing the financial sector with the software toolsets available to analysts. The credit decisions you make are dependent on the data, models, and tools that you use to determine them. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications combines both theoretical explanation and practical applications to define as well as demonstrate how you can build credit risk models using SAS Enterprise Miner and SAS/STAT and apply them into practice. The ultimate goal of credit risk is to reduce losses through better and more reliable credit decisions that can be developed and deployed quickly. In this example-driven book, Dr. Brown breaks down the required modeling steps and details how this would be achieved through the implementation of SAS Enterprise Miner and SAS/STAT. Users will solve real-world risk problems as well as comprehensively walk through model development while addressing key concepts in credit risk modeling. The book is aimed at credit risk analysts in retail banking, but its applications apply to risk modeling outside of the retail banking sphere. Those who would benefit from this book include credit risk analysts and managers alike, as well as analysts working in fraud, Basel compliancy, and marketing analytics. It is targeted for intermediate users with a specific business focus and some programming background is required. Efficient and effective management of the entire credit risk model lifecycle process enables you to make better credit decisions. Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications demonstrates how practitioners can more accurately develop credit risk models as well as implement them in a timely fashion.