Regression Models And Decision Trees With Sas Enterprise Miner
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Regression Models and Decision Trees with SAS Enterprise Miner
Author | : Scientific Books |
Publsiher | : CreateSpace |
Total Pages | : 188 |
Release | : 2015-06-22 |
Genre | : Electronic Book |
ISBN | : 1514651475 |
Download Regression Models and Decision Trees with SAS Enterprise Miner Book in PDF, Epub and Kindle
SAS Institute implements data mining in Enterprise Miner software, which will be used in this book focused in Sampling Tecniques, Exploratory Analysis and Association Rules. 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.
Decision Trees With SAS Enterprise Miner
Author | : Scientific Books |
Publsiher | : Createspace Independent Publishing Platform |
Total Pages | : 196 |
Release | : 2016-01-02 |
Genre | : Electronic Book |
ISBN | : 1523218150 |
Download Decision Trees With SAS Enterprise Miner Book in PDF, Epub and Kindle
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.
Predictive Modeling with SAS Enterprise Miner
Author | : Kattamuri S. Sarma |
Publsiher | : SAS Institute |
Total Pages | : 574 |
Release | : 2017-07-20 |
Genre | : Computers |
ISBN | : 9781635260403 |
Download Predictive Modeling with SAS Enterprise Miner Book in PDF, Epub and Kindle
« 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. »--
Decision Trees for Analytics Using SAS Enterprise Miner
Author | : Barry De Ville,Padraic Neville |
Publsiher | : Unknown |
Total Pages | : 268 |
Release | : 2019-07-03 |
Genre | : Computers |
ISBN | : 164295313X |
Download Decision Trees for Analytics Using SAS Enterprise Miner Book in PDF, Epub and Kindle
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 |
Publsiher | : SAS Press |
Total Pages | : 224 |
Release | : 2006 |
Genre | : Business & Economics |
ISBN | : 1590475674 |
Download Decision Trees for Business Intelligence and Data Mining Book in PDF, Epub and Kindle
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.
Data Mining Techniques Predictive Models with SAS Enterprise Miner
Author | : Scientific Books |
Publsiher | : CreateSpace |
Total Pages | : 332 |
Release | : 2015-05-08 |
Genre | : Electronic Book |
ISBN | : 151210003X |
Download Data Mining Techniques Predictive Models with SAS Enterprise Miner Book in PDF, Epub and Kindle
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
Data Mining With SAS Enterprise Miner Predictive Techniques
Author | : C. Perez |
Publsiher | : Createspace Independent Publishing Platform |
Total Pages | : 268 |
Release | : 2017-10-17 |
Genre | : Electronic Book |
ISBN | : 1978373627 |
Download Data Mining With SAS Enterprise Miner Predictive Techniques Book in PDF, Epub and Kindle
The essential aim of this book is to use predictive models for Data Mning. Models of decision trees, regression and neural networks are used to predict various 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 Data Mining. 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 Miming tools are used to build the main models: Decision Tree, Neural Network, and Regression. These are addressed in considerable detail, with numerous examples of practical business applications that are illustrated with tables, charts, displays, equations, and even manual calculations that let you see the essence of what Enterprise Miner is doing when it estimates or optimizes a given model.
Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner
Author | : Olivia Parr-Rud |
Publsiher | : SAS Institute |
Total Pages | : 182 |
Release | : 2014-10 |
Genre | : Computers |
ISBN | : 9781629593272 |
Download Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner Book in PDF, Epub and Kindle
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. --