Neural Network Modeling Using Sas Enterprise Miner

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Neural Network Modeling Using SAS Enterprise Miner

Randall Matignon
Neural Network Modeling Using SAS Enterprise Miner Book PDF

Author : Randall Matignon
Publisher : AuthorHouse
Page : 608 pages
File Size : 50,7 Mb
Release : 2005-08
Category : Computers
ISBN : 9781418423414

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Neural Network Modeling Using SAS Enterprise Miner by Randall Matignon Pdf

This book is designed in making statisticians, researchers, and programmers aware of the awesome new product now available in SAS called Enterprise Miner. The book will also make readers get familiar with the neural network forecasting methodology in statistics. One of the goals to this book is making the powerful new SAS module called Enterprise Miner easy for you to use with step-by-step instructions in creating a Enterprise Miner process flow diagram in preparation to data-mining analysis and neural network forecast modeling. Topics discussed in this book An overview to traditional regression modeling. An overview to neural network modeling. Numerical examples of various neural network designs and optimization techniques. An overview to the powerful SAS product called Enterprise Miner. An overview to the SAS neural network modeling procedure called PROC NEURAL. Designing a SAS Enterprise Miner process flow diagram to perform neural network forecast modeling and traditional regression modeling with an explanation to the various configuration settings to the Enterprise Miner nodes used in the analysis. Comparing neural network forecast modeling estimates with traditional modeling estimates based on various examples from SAS manuals and literature with an added overview to the various modeling designs and a brief explanation to the SAS modeling procedures, option statements, and corresponding SAS output listings.

Predictive Modeling with SAS Enterprise Miner

Kattamuri S. Sarma
Predictive Modeling with SAS Enterprise Miner Book PDF

Author : Kattamuri S. Sarma
Publisher : SAS Institute
Page : 574 pages
File Size : 44,7 Mb
Release : 2017-07-20
Category : Computers
ISBN : 9781635260403

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Predictive Modeling with SAS Enterprise Miner by Kattamuri S. Sarma Pdf

« 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. »--

Data Mining Using SAS Enterprise Miner

Randall Matignon
Data Mining Using SAS Enterprise Miner Book PDF

Author : Randall Matignon
Publisher : John Wiley & Sons
Page : 584 pages
File Size : 50,8 Mb
Release : 2007-08-03
Category : Mathematics
ISBN : 9780470149010

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Data Mining Using SAS Enterprise Miner by Randall Matignon Pdf

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.

Neural Networks with SAS Enterprise Miner

Scientific Books
Neural Networks with SAS Enterprise Miner Book PDF

Author : Scientific Books
Publisher : CreateSpace
Page : 292 pages
File Size : 40,5 Mb
Release : 2015-06-22
Category : Electronic
ISBN : 1514652285

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Neural Networks with SAS Enterprise Miner by Scientific Books Pdf

SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused in Neural Networks models. 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 Techniques. Predictive Models with SAS Enterprise Miner

Scientific Books
Data Mining Techniques Predictive Models with SAS Enterprise Miner Book PDF

Author : Scientific Books
Publisher : CreateSpace
Page : 332 pages
File Size : 47,6 Mb
Release : 2015-05-08
Category : Electronic
ISBN : 151210003X

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Data Mining Techniques. Predictive Models with SAS Enterprise Miner by Scientific Books Pdf

SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused predictive models. 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. The essential content of the book is as follows: SAS ENTERPRISE MINER WORKING ENVIRONMENT MODELLING PREDICTIVE TECHNIQUES WITH SAS ENTERPRISE MINER REGRESSION NODE: MULTIPLE REGRESSION MODEL LOGISTIC REGRESSION DMINE REGRESSION NODE PARTIAL LEAST SQUARES NODE. PLS REGRESSION LARS NODE CLASSIFICATION PREDICTIVE TECHNIQUES. DECISION TREES WITH SAS ENTERPRISE MINER DECISION TREE NODE PREDICTIVE MODELS WITH NEURAL NETWORKS WITH SAS ENTERPRISE MINER OPTIMIZATION AND ADJUSTMENT OF MODELS WITH NETS: NEURAL NETWORK NODE SIMPLE NEURAL NETWORKS PERCEPTRONS HIDDEN LAYERS MULTILAYER PERCEPTRONS (MLPS) RADIAL BASIS FUNCTION (RBF) NETWORKS SCORING AUTONEURAL NODE NETWORK ARCHITECTURES NEURAL NODE TWOSTAGE NODE GRADIENT BOOSTING NODE MEMORY-BASED REASONING (MBR) NODE RULE INDUCTION NODE ENSEMBLE NODE COMBINING MODELS USING THE ENSEMBLE NODE MODEL IMPORT NODE SVM NODE ASSESS PHASE IN DATA MINING PROCESS CUTOFF NODE DECISIONS NODE MODEL COMPARISON NODE SCORE NODE

Getting Started with SAS Enterprise Miner 13. 1

SAS Institute
Getting Started with SAS Enterprise Miner 13 1 Book PDF

Author : SAS Institute
Publisher : Unknown
Page : 82 pages
File Size : 43,5 Mb
Release : 2013-12
Category : Mathematics
ISBN : 1612905528

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Getting Started with SAS Enterprise Miner 13. 1 by SAS Institute Pdf

Introduces the core functionality of SAS Enterprise Miner and shows how to perform basic data mining tasks. Provides step-by-step examples that create a complete process-flow diagram including graphic results. Introduces the core functionality of SAS Enterprise Miner and shows how to perform basic data mining tasks. Provides step-by-step examples that create a complete process-flow diagram including graphic results.

Predictive Modeling with SAS Enterprise Miner

Kattamuri S. Sarma
Predictive Modeling with SAS Enterprise Miner Book PDF

Author : Kattamuri S. Sarma
Publisher : Unknown
Page : 0 pages
File Size : 50,9 Mb
Release : 2013-12
Category : Business
ISBN : 1607647672

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Predictive Modeling with SAS Enterprise Miner by Kattamuri S. Sarma Pdf

Learn the theory behind and methods for predictive modeling using SAS Enterprise Miner. Learn how to produce predictive models and prepare presentation-quality graphics in record time with Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Second Edition. If you are a graduate student, researcher, or statistician interested in predictive modeling; a data mining expert who wants to learn SAS Enterprise Miner; or a business analyst looking for an introduction to predictive modeling using SAS Enterprise Miner, you'll be able to develop predictive models quickly and effectively using the theory and examples presented in this book. Author Kattamuri Sarma offers the theory behind, programming steps for, and examples of predictive modeling with SAS Enterprise Miner, along with exercises at the end of each chapter. You'll gain a comprehensive awareness of how to find solutions for your business needs. This second edition features expanded coverage of the SAS Enterprise Miner nodes, now including File Import, Time Series, Variable Clustering, Cluster, Interactive Binning, Principal Components, AutoNeural, DMNeural, Dmine Regression, Gradient Boosting, Ensemble, and Text Mining. Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner. This book is part of the SAS Press program.

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Olivia Parr-Rud
Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner Book PDF

Author : Olivia Parr-Rud
Publisher : SAS Institute
Page : 182 pages
File Size : 48,5 Mb
Release : 2014-10
Category : Computers
ISBN : 9781629593272

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Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner by Olivia Parr-Rud Pdf

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

Kattamuri S. Sarma
Predictive Modeling with SAS Enterprise Miner Book PDF

Author : Kattamuri S. Sarma
Publisher : SAS Institute
Page : 574 pages
File Size : 51,6 Mb
Release : 2017-07-20
Category : Computers
ISBN : 9781635260380

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Predictive Modeling with SAS Enterprise Miner by Kattamuri S. Sarma Pdf

A step-by-step guide to predictive modeling! Kattamuri Sarma's Predictive Modeling with SAS Enterprise Miner: Practical Solutions for Business Applications, Third Edition, will show you how to develop and test predictive models quickly using SAS Enterprise Miner. Using realistic data, the book explains complex methods in a simple and practical way to readers from different backgrounds and industries. Incorporating the latest version of Enterprise Miner, this third edition also expands the section on time series. 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. Topics covered include logistic regression, regression, decision trees, neural networks, variable clustering, observation clustering, data imputation, binning, data exploration, variable selection, variable transformation, and much more, including analysis of textual data. Develop predictive models quickly, learn how to test numerous models and compare the results, gain an in-depth understanding of predictive models and multivariate methods, and discover how to do in-depth analysis. Do it all with Predictive Modeling with SAS Enterprise Miner!

Data Science and Machine Learning for Non-Programmers

Dothang Truong
Data Science and Machine Learning for Non Programmers Book PDF

Author : Dothang Truong
Publisher : CRC Press
Page : 768 pages
File Size : 55,6 Mb
Release : 2024-02-23
Category : Business & Economics
ISBN : 9781003835639

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Data Science and Machine Learning for Non-Programmers by Dothang Truong Pdf

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.

Data Mining Techniques. Segmentation with SAS Enterprise Miner

Scientific Books
Data Mining Techniques Segmentation with SAS Enterprise Miner Book PDF

Author : Scientific Books
Publisher : CreateSpace
Page : 288 pages
File Size : 52,6 Mb
Release : 2015-05-08
Category : Electronic
ISBN : 1512098000

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Data Mining Techniques. Segmentation with SAS Enterprise Miner by Scientific Books Pdf

SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused segmentation tasks. 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. The essential content of the book is as follows: SAS ENTERPRISE MINER WORKING ENVIRONMENTSEGMENTATION PREDICTIVE TECHNIQUES MODELING PREDICTIVE TECHNIQUES FOR SEGMENTATION REGRESSION NODE: MULTIPLE REGRESSION MODEL LOGISTIC REGRESSION DMINE REGRESSION NODE SEGMENTATION PREDICTIVE TECHNIQUES. DECISION TREES DECISION TREE NODE DECISION TREE INTERACTIVE TRAINING DECISION TREE NODE OUTPUT DATA SOURCES GRADIENT BOOSTING NODE SEGMENTATION PREDICITIVE MODELS WITH NEURAL NETWORKS NEURAL NETWORKS FOR SEGMENTATION OPTIMIZATION AND ADJUSTMENT OF SEGMENTATION MODELS WITH NETS: NEURAL NETWORK NODE SIMPLE NEURAL NETWORKS PERCEPTRONS HIDDEN LAYERS MULTILAYER PERCEPTRONS (MLPS) RADIAL BASIS FUNCTION (RBF) NETWORKS LOCAL PROCESSING NETWORKS SCORING NEURAL NETWORK NODE TRAIN PROPERTIES NEURAL NETWORK NODE RESULTS AUTONEURAL NODE NETWORK ARCHITECTURES DM NEURAL NODE ENSEMBLE NODE SEGMENTATION DESCRIPTIVE TECHNIQUES. CLUSTER ANALYSIS CLUSTER ANALYSIS ON ENTERPRISE MINER CLUSTER NODE SOM/KOHONEN NODE VARIABLE CLUSTERING NODE PREDICTIVE MODELING WITH VARIABLE CLUSTERING EXAMPLE ASSESS PHASE IN SEGMENTATION PREDICTIVE MODELS CUTOFF NODE SCORE NODE SEGMENT PROFILE NODE

Data Science and Machine Learning for Non-Programmers

Dothang Truong
Data Science and Machine Learning for Non Programmers Book PDF

Author : Dothang Truong
Publisher : CRC Press
Page : 590 pages
File Size : 46,8 Mb
Release : 2024-02-23
Category : Business & Economics
ISBN : 9781003835615

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Data Science and Machine Learning for Non-Programmers by Dothang Truong Pdf

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize machine learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. Designed as a guiding companion for both beginners and experienced practitioners, this book targets a wide audience, including students, lecturers, researchers, and industry professionals from various backgrounds.

Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner

Olivia Parr-Rud
Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner Book PDF

Author : Olivia Parr-Rud
Publisher : SAS Institute
Page : 231 pages
File Size : 43,8 Mb
Release : 2014-10-01
Category : Computers
ISBN : 9781629593289

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Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner by Olivia Parr-Rud Pdf

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. Today’s businesses increasingly use data to drive decisions that keep them competitive. Especially with the influx of big data, the importance of data analysis to improve every dimension of business cannot be overstated. Data analysts are therefore in demand; however, many hires and prospective hires, although talented with respect to business and statistics, lack the know-how to perform business analytics with advanced statistical software. Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner is a beginner’s guide with clear, illustrated, step-by-step instructions that 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. This book is part of the SAS Press program.

Statistical Data Mining Using SAS Applications

George Fernandez
Statistical Data Mining Using SAS Applications Book PDF

Author : George Fernandez
Publisher : CRC Press
Page : 477 pages
File Size : 49,7 Mb
Release : 2010-06-18
Category : Business & Economics
ISBN : 9781439810767

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Statistical Data Mining Using SAS Applications by George Fernandez Pdf

Statistical Data Mining Using SAS Applications, Second Edition describes statistical data mining concepts and demonstrates the features of user-friendly data mining SAS tools. Integrating the statistical and graphical analysis tools available in SAS systems, the book provides complete statistical data mining solutions without writing SAS program co

PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES

Anonim
PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS REGRESSION AND DECISION TREES Book PDF

Author : Anonim
Publisher : CESAR PEREZ
Page : 222 pages
File Size : 50,9 Mb
Release : 2024-06-16
Category : Electronic
ISBN : 9781008979529

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PREDICTIVE MODELS TO RISK ANALYSIS WITH NEURAL NETWORKS. REGRESSION AND DECISION TREES by Anonim Pdf

The essential aim of this book is to use predictive models to analyze risk. Models of decision trees, regression and neural networks are used to predict various risk categories. This book shows you how to build decision tree models to predict a categorical target and how to build regression tree models and neural network models to predict a continuous target. Successive chapters present examples that clarify the application of the models in the field of risk. The examples are solved step by step with SAS Enterprise Miner in order to make easier the understanding of the methodologies used. The book begins by introducing the basics of creating a project, manipulating data sources, and navigating through different results windows. Data Mining tools are used to build the main risk models: Decision Tree, Neural Network, and Regression.