Data Mining Using Sas Enterprise Miner
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Data Mining Using Sas Enterprise Miner
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Author : Randall Matignon
language : en
Publisher: John Wiley & Sons
Release Date : 2007-08-03
Data Mining Using Sas Enterprise Miner written by Randall Matignon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-03 with Mathematics categories.
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.
Introduction To Data Mining Using Sas Enterprise Miner
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Author : Patricia B. Cerrito
language : en
Publisher: SAS Press
Release Date : 2006
Introduction To Data Mining Using Sas Enterprise Miner written by Patricia B. Cerrito and has been published by SAS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Data mining categories.
"This manual provides a general, practical introduction to data mining using SAS Enterprise Miner and SAS Text Miner software"--Preface.
Data Mining Using Sas Enterprise Miner
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Author : SAS Institute
language : en
Publisher: Sas Inst
Release Date : 2003
Data Mining Using Sas Enterprise Miner written by SAS Institute and has been published by Sas Inst this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
Unknown Mir Title
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Author : SAS Publishing
language : en
Publisher:
Release Date : 2001-03
Unknown Mir Title written by SAS Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-03 with categories.
Decision Trees For Business Intelligence And Data Mining
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Author : Barry De Ville
language : en
Publisher: SAS Press
Release Date : 2006
Decision Trees For Business Intelligence And Data Mining written by Barry De Ville and has been published by SAS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Business & Economics categories.
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.
Getting Started With Sas Enterprise Miner 6 1
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Author : SAS Institute
language : en
Publisher: Sas Inst
Release Date : 2009
Getting Started With Sas Enterprise Miner 6 1 written by SAS Institute and has been published by Sas Inst this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Computers categories.
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.
Data Mining Techniques With Sas Enterprise Miner Sampling Exporatory Analysis And Association Rules
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Author : Scientific Books
language : en
Publisher: CreateSpace
Release Date : 2015-06-22
Data Mining Techniques With Sas Enterprise Miner Sampling Exporatory Analysis And Association Rules written by Scientific Books and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-22 with categories.
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.
First Steps In Data Mining With Sas Enterprise Miner
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Author : Martha Abell
language : en
Publisher: CreateSpace
Release Date : 2014-09-06
First Steps In Data Mining With Sas Enterprise Miner written by Martha Abell and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-06 with categories.
SAS Enterprise Miner streamlines the data mining process to create highly accurate predictive and descriptive models based on analysis of vast amounts of data from across an enterprise. Data mining is applicable in a variety of industries and provides methodologies for such diverse business problems as fraud detection, householding, customer retention and attrition, database marketing, market segmentation, risk analysis, affinity analysis, customer satisfaction, bankruptcy prediction, and portfolio analysis. In SAS Enterprise Miner, the data mining process has the following (SEMMA) steps: Sample the data by creating one or more data sets. The sample should be large enough to contain significant information, yet small enough to process. This step includes the use of data preparation tools for data import, merge, append, and filter, as well as statistical sampling techniques. Explore the data by searching for relationships, trends, and anomalies in order to gain understanding and ideas. This step includes the use of tools for statistical reporting and graphical exploration, variable selection methods, and variable clustering. Modify the data by creating, selecting, and transforming the variables to focus the model selection process. This step includes the use of tools for defining transformations, missing value handling, value recoding, and interactive binning. Model the data by using the analytical tools to train a statistical or machine learning model to reliably predict a desired outcome. This step includes the use of techniques such as linear and logistic regression, decision trees, neural networks, partial least squares, LARS and LASSO, nearest neighbor, and importing models defined by other users or even outside SAS Enterprise Miner. Assess the data by evaluating the usefulness and reliability of the findings from the data mining process. This step includes the use of tools for comparing models and computing new fit statistics, cutoff analysis, decision support, report generation, and score code management. You might or might not include all of the SEMMA steps in an analysis, and it might be necessary to repeat one or more of the steps several times before you are satisfied with the results. After you have completed the SEMMA steps, you can apply a scoring formula from one or more champion models to new data that might or might not contain the target variable. Scoring new data that is not available at the time of model training is the goal of most data mining problems. Furthermore, advanced visualization tools enable you to quickly and easily examine large amounts of data in multidimensional histograms and to graphically compare modeling results.
Sas Enterprise Miner Data Mining Techniques
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Author : Martha Abell
language : en
Publisher: CreateSpace
Release Date : 2014-09-05
Sas Enterprise Miner Data Mining Techniques written by Martha Abell and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-05 with categories.
This book presents the most common techniques used in data mining in a simple and easy to understand way through one of the most common software solutions from existing in the market, namely the SAS software. It seeks to clarify the original purpose as related applications traditionally qualified as difficult or opaque methods. It seeks to present applications of data mining without handle high theoretical mathematical developments or complicated algorithms, which is the most common reason for the difficulties in understanding and application of this material. In the text the concepts of data mining in the simplest way possible, so as to be intelligible to readers with diverse backgrounds are described. The chapter begins by describing the techniques presented in accessible language and then how to address them through practical applications.
Predictive Modeling With Sas Enterprise Miner
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Author : Kattamuri S. Sarma
language : en
Publisher: SAS Institute
Release Date : 2017-07-20
Predictive Modeling With Sas Enterprise Miner written by Kattamuri S. Sarma and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-20 with Computers categories.
« 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. »--