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410 papers and 45 presentations; 429 titles.

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Conference × Year × Title × Authors Extras Pages
PharmaSUG CN 2026 Modernizing the Vaccine TAUG: An End-to-End, Output-Driven Framework for Reactogenicity, Immunogenicity, Efficacy, and Reviewer-Ready Submissions Lin Chen,
Jialiang Liu		 source 18
PharmaSUG 2026 From Exploratory Data Analysis to Machine Learning: Continuing My Python Journey Leon Rod Davoody source 13
MWSUG 2025 Code Smarter, Not Harder: The 5 C's of ChatGPT for the SASsy Professional Kirk Paul Lafler,
Charu Shankar		 source 49
SESUG 2025 The Missing Piece Cali M. Davis 17
PharmaSUG 2025 Code Smarter, Not Harder: The 5 C's of ChatGPT for the SASsy Professional Charu Shankar,
Kirk Paul Lafler		 source 49
PharmaSUG 2025 Comparing SQL and Graph Database Query Methods for Answering Clinical Trial Questions with LLM-Powered Pipelines Jaime Yan source 24
MWSUG 2024 Charting Your Organization's Machine Learning Roadmap Ryan Paul Lafler source 7
MWSUG 2024 Create Report with SAS Visual Analytics to Finish Your SAS Story [presentation] Shinya Kodama source 25
MWSUG 2024 Introduction to Machine Learning in SAS [presentation] Melodie Rush source 71
PHUSE EU 2024 Leveraging 'Ensemble' Machine Learning Models to Drive Automation of Specification Generation and Data Mapping in Clinical Trial Data Submission Venu Mallarapu source
presentation source		 10
SESUG 2024 Charting Your Organization's Machine Learning Roadmap Ryan Paul Lafler source 7
SESUG 2024 Unlocking Insights: Harnessing Supervised Machine Learning for Advanced Data Analysis Vindhya Hegde source 23
WUSS 2024 Airbnb Consumer Behavior Analysis Evelyn Larson,
Anabeli Chandra		 source 14
WUSS 2024 Charting Your Organization's Machine Learning Roadmap Ryan Paul Lafler source 6
WUSS 2024 Flight Delay Analysis and Prediction Eric C Braga,
Miguel Ángel Bravo Martínez del Valle,
Riley Rutan,
Fernanda Carrillo		 source 19
WUSS 2024 SAS Viya in Action: Enhancing Life Sciences Data Analysis [presentation] Matthew J. Becker source 13
PHUSE US 2024 Novel Analytics for Risk-Based Monitoring: Harnessing Natural Language Processing for Query Data to Enhance and Optimise Data Quality Lawrence Dennison-Hall,
Mariia Lapaeva		 source
presentation source		 14
PHUSE US 2024 Risk-Based Monitoring Using AI/ML Detection of Systematic Bias in Clinical Data Kostiantyn Drach,
Sergey Glushakov		 source
presentation source		 12
PHUSE US 2024 Utilising Machine Learning Algorithms to Detect the Outlier or Inconsistencies in the Analysis Results in Datasets and Summary Reports Weiwei Xu,
Linshan Yuan		 source
poster source		 5
PHUSE EU 2023 Get the Full Picture of Your Data with SAS Andy Bayliss source
presentation source		 13
WUSS 2023 Introduction to Machine Learning - Descriptions and Best Practices Jim Box source 13
SESUG 2023 Binning Predictors for Logistic Regression Bruce S. Lund source 25
SESUG 2023 Is Rushing in the Modern NFL a Viable Option? Alex Mason source 8
PharmaSUG 2023 What is Machine Learning, anyway? Jim Box source 11
PHUSE US 2023 Recommender System for Study Build: Using the Protocol to Select CRFs from Standard Libraries Komal Govil,
Karan Pande		 source
presentation source		 4
SESUG 2022 Don't be so One-Dimensional: How to Engineer Multi-Dimensional, High Cardinality Categorical Inputs for Machine Learning Aleksandar Nikolic source 25
WUSS 2022 Story telling with SAS Visual Statistics Jim Box,
Laura Watson		 source 8
PharmaSUG 2022 Generating Real World Evidence On The Likelihood Of Metastatic Cancer In Patients Through Machine Learning In Observational Research: Insights For Prevention Sherrine Eid,
Samiul Haque,
S. Robert Collins		 source 8
PharmaSUG 2022 Introduction to Synthetic Control Arm Venkat Rajagopal,
Abhinav Jain		 source 4
PharmaSUG 2022 Potential features analysis affect Covid-19 spread Yida Bao,
Philippe Gaillard		 source 11
PHUSE US 2022 Machine Learning in R to Predict Outcomes from Biomarker Data [presentation] Benno F. Kurch,
Prakash Dev		 source
video		 21
PHUSE EU 2021 HoW: RWD Applications in Pharma with a Focus on Clinical Trials [presentation] Berber Snoeijer,
Samiul Haque		 source 47
SESUG 2021 Statistical Test Selector (STS) For Researchers Kannan Deivasigamani,
Douglas Lunsford		 source 11
SESUG 2021 Use SAS Enterprise Miner Workstation 15.1 to Do Predictive Analysis for Mobile Strategy Games Industry Chun Du source 11
PharmaSUG 2021 Random Forest Machine Learning Application using R Shiny for Project Timeline Forecasting Hrideep Antony,
Aman Bahl		 source 8
SGF 2021 Detecting Online Recruitment Fraud Matthew Fruge,
Noah Heinrich		 source 6
SGF 2021 Next-Generation Data Mining and Machine Learning: Python and SAS Together at Last George S. Habek,
Suman Kumar Das		 source
presentation		 24
SESUG 2020 Model Comparison of Machine Learning Techniques to detect signs of Penetrating Abdominal and Pelvic Injuries using Base JMP and R Integration Melvin T. Alexander source 25
SGF 2020 A Data-driven Approach to Understand Mild Cognitive Impairment from Imbalanced Data Using SAS [presentation] Liyuan Liu,
Meng Han,
Yiyun Zhou,
Gita Taasoobshirazi		 source 5
SGF 2020 Analyzing Non-normal Data: Application to Missing Data Problems Niloofar Ramezani source 10
SGF 2020 Apply the Key Ideas from Andrew Ng's Machine Learning Certification (Coursera) in SAS Viya Petri Roine source 9
SGF 2020 Automation in SAS Visual Data Mining and Machine Learning Wendy Czika source 26
SGF 2020 Developing Credit Scores with Telco Data Using Machine Learning and Agile Methodology Luciano Diettrich source 14
SGF 2020 Exploring Online Drug Reviews using Text Analytics, Sentiment Analysis, and Data Mining Models Thu Dinh,
Goutam Chakraborty		 source 23
SGF 2020 How to Explain Your Black-Box Models in SAS Viya Funda Güneş source 26
SGF 2020 Hybrid Marketing, Campaign Management, and Analytics' Last Mile Using SAS Customer Intelligence 360 Suneel Grover source 32
SGF 2020 Modelling Imbalanced Classes Humphrey Brydon source 6
SGF 2020 Relationship analysis and customer churn forecasting in a financial cooperative institution Carolina Silva,
Brunno Sousa Ramos		 source 7
SGF 2020 Smarter and Faster with SAS Visual Analytics Rick Styll source 13
SGF 2020 The Plight of the Honeybee Rachael Bishop source 8
SGF 2020 The Seven Most Popular Machine Learning Algorithms for Online Fraud Detection and Their Use in SAS Patrick Maher source 6
SGF 2020 Turning the Crank. A Simulation of Optimizing Model Retraining David R. Duling source 17
SGF 2020 Using Analytics to Predict Tax Recovery and Prioritize Audits and Investigations in Canada Jason A. Oliver source 19
SGF 2020 What Happens After Police Shootings? Aravind Dhanabal source 7
PharmaSUG 2020 Detecting Side Effects and Evaluating the Effectiveness of Drugs from Customers' Online Reviews using Text Analytics, Sentiment Analysis and Machine Learning Models Thu Dinh,
Goutam Chakraborty		 source 22
PharmaSUG 2020 How to let Machine Learn Clinical Data Review as it can Support Reshaping the Future of Clinical Data Cleaning Process Mirai Kikawa,
Yuichi Nakajima		 source 9
PHUSE US 2020 A Comparison of Machine Learning Algorithms for Binary Classification of Free-text Fields Using SAS, R, and Python Michael S Rimler source
presentation source		 12
PHUSE US 2020 Interactive Real-world Data Analysis Using Machine Learning Algorithms James J. Kim source
poster source		 5
PHUSE US 2020 Is Artificial Intelligence our destiny? Data-driven Decision-making in a Dynamic Landscape using SAS Viya Aman Bahl,
Hrideep Antony		 source
presentation source		 13
PHUSE EU 2019 SMART RPA - powered by Machine Learning Charan Kumar Kuyyamudira Janardhana source
presentation source		 10
SESUG 2019 Advanced Statistical Modeling within Machine Learning and Big Data Analytics Niloofar Ramezani,
George Mason		 source 16
SESUG 2019 Analyzing Airbnb reviews using SAS Text Miner and Predicting the factors contributing for higher ratings Ashlesha Sampathi source 15
SESUG 2019 Hybrid Rare Event Sampling Technique Ross Bettinger source 15
SESUG 2019 Summarizing some conventional methods to classify a binary target Yida Bao,
Philippe Gaillard		 source 10
SESUG 2019 Validating Classification and Recidivism in Corrections Through Outcome Analytics Alan R. Mann source 34
SCSUG 2019 Can Life Style Change Prevent Diabetes? Mounica Mandapati source 11
SCSUG 2019 Pattern Analysis and Predictive Policing Using Socio-Economic Factors Trishla Mishra source 12
SCSUG 2019 Uplift Modeling in Retail Marketing using SAS Aashish Arjan Bugalia,
Agastya Komarraju,
Miriam McGaugh		 source 15
MWSUG 2019 Classifying Risk in Life Insurance using Predictive Analytics Sai Gopi Krishna Govindarajula 6
MWSUG 2019 Detecting Side Effects and Evaluating Effectiveness of Drugs from Customers' Online Reviews using Text Analytics and Data Mining Models Thu Dinh 23
MWSUG 2019 Do undergraduates need prerequisites for common courses? Lin Qi,
Archana Chinnaswamy,
Miriam McGaugh		 6
MWSUG 2019 Logistic Regression, Basics and Beyond Bruce S. Lund 35
MWSUG 2019 US Airline Passenger Satisfaction using SAS Enterprise Miner Harish Reddy Patlolla,
Miriam McGaugh		 12
WUSS 2019 Decision Trees: a Gentle Introduction Richard D. Hector source 11
WUSS 2019 Multi-Way (more than two) Splits In Decision Trees Russell M. Lavery source 8
WUSS 2019 PROC DTREE VS PROC HPSPLIT YuTing Tian source 19
WUSS 2019 Telecom Industry: Customer Churn Prediction Aakash Dwivedi source 7
PharmaSUG 2019 An Introduction to the Process of Improving a Neural Network YuTing Tian source 22
PharmaSUG 2019 Performing Analytics on Free-Text Data Fields: A Programer-s Wurst Nitemare Michael S Rimler,
Matt Pitlyk		 source 18
PharmaSUG 2019 Using Real-World Evidence to Affect the Opioid Crisis Sherrine Eid,
Andrea Coombs		 source 10
SGF 2019 A Comparison of Algorithmic and Epidemiologic Approaches for Modeling Predictors of Type II Diabetes Audrey Whittle source 8
SGF 2019 AI is Coming for Your BI: Automated Analysis in SAS Visual Analytics Rick Styll source 19
SGF 2019 Airbnb New York City: Demystifying the Superhost Program Soumya Ranjan Kar Choudhury source 7
SGF 2019 An Introduction to the Process of Improving a Neural Network YuTing Tian source 22
SGF 2019 Asking the Right Questions: A study in Multiclass Imbalanced Classification for H1-B Visas Matthew Bunker,
Owen Kelly		 source 7
SGF 2019 Detecting Fraud and Other Anomalies Using Isolation Forests Ryan Gillespie source 6
SGF 2019 Distribution Transformer Health Monitoring and Predictive Asst Maintenance Prasenjit Shil,
Tom Anderson		 source 11
SGF 2019 Enabling SAS Software to Communicate RESTfully with Cloud Services Tom Caswell,
Fred Burke		 source 14
SGF 2019 Factors Affecting Mental Health in Employees and Their Relation to Suicide Rates at a Workplace Shambhavi Pandey source 11
SGF 2019 Factors Influencing Academic Performance Onkar Mayekar,
Miriam McGaugh		 source 9
SGF 2019 From Words to Actions: Using Text Analytics to Drive Business Decisions Reid Baughman source 7
SGF 2019 Improve Your AML Monitoring While Reducing Costs with SAS Viya Calvin Crase,
Chris St. Jeor		 source 11
SGF 2019 Kustomizing Your Viya Engine Using SAS Studio Custom Tasks and D3.js Elliot Inman,
Ryan West,
Olivia Wright		 source 16
SGF 2019 Machine Learning and Predictive Analytics in SAS Enterprise Miner and SAS/STAT Software David Richard Cutler source 21
SGF 2019 Open Visualization with SAS Viya and Python Joseph Indelicato source 12
SGF 2019 Playing Favorites: Our Top 10 Model Studio Features in SAS Visual Data Mining and Machine Learning Wendy Czika,
Peter Gerakios		 source 16
SGF 2019 SAS on Kubernetes: Container Orchestration of Analytic Work Loads Sumanth Yamala source 6
SGF 2019 The Relationship Between Social Determinants of Health and Healthcare Utilization Ryan C. Butterfield,
Melissa Gottschalk,
Laura Soloway,
Paul A. LaBrec		 source 16
SGF 2019 Using Simulation Games to Teach Analytics Jean-François Plante,
Pierre-Majorique Léger,
Jean-François Michon,
Forough Karimi-Alaghehband,
Marc Fredette,
Michael Bliemel		 source 7
PHUSE US 2019 Artificial Intelligence and Healthcare Aman Bahl,
Hrideep Antony		 source
presentation source		 10
PHUSE US 2019 Quantifying Dynamic Risk with Predictive Analytics Susan Olson,
Connor English		 source
presentation source		 7
SCSUG 2018 City of Austin Community Perception and Satisfaction Analysis Eric Hart source 11
SCSUG 2018 How to configure Python and SASPY Michael McCarthy source 7
SCSUG 2018 Machine Learning in Litigation Prediction - Workers' Compensation Litigation Propensity Predictive Model Mei Najim source 17
SCSUG 2018 NBA Draft Analytics: Boom or Bust? Isaiah Hartman source 17
SCSUG 2018 Predicting the Federal Reserve?s Next Federal Funds Rate Decisions Nhan Nguyen source 13
PHUSE EU 2018 Using SAS Advanced Analytic to Gain Insight into the Opioid Epidemic [presentation] Andy Bayliss source 17
SESUG 2018 ANALYSIS OF FACTORS INFLUENCING DROPOUTS IN SOPHOMORE ENROLLMENT Apoorva Chandrasekaran source 14
SESUG 2018 Fight Human Trafficking with Text Analytics Stuti Mehrotra,
Miriam McGaugh		 source 10
SESUG 2018 Predicting the Risk of Attrition for Undergraduate Students using SAS Enterprise Miner Sivateja Reddy Kandula source 12
SESUG 2018 Undergraduate Student Retention, Can we catch them before they fall? Lohit Bhandari source 6
MWSUG 2018 Addressing Opioid Crisis using Data Science Rishabh Mishra 5
MWSUG 2018 An introduction to classification and regression trees with PROC HPSPLIT. Peter L. Flom 13
MWSUG 2018 An Introduction to the Process of Improving a Neural Network YuTing Tian 22
MWSUG 2018 Genocide Modeling - Historical Risk Factors and Odds Ratios David J. Corliss 5
PHUSE US 2018 Drug-Induced Liver Injury (DILI) Classification Using FDA-Approved Drug Labeling and FAERS Data - FDA Qais Hatim source
presentation source		 31
PHUSE US 2018 Modeling and Text Analysis to Empower FAERS Adverse Event Mitigation Qais Hatim,
Emily McRae		 source
presentation source		 24
PharmaSUG 2018 Build Models without Code with the new SAS Visual Interface Jim Box source 12
PharmaSUG 2018 Visualizing and Modeling Clinical Trial Data Alex Ford,
Andrea Coombs		 source 7
SGF 2018 A Cautionary Tale of Using Machine Learning within Credit Risk in the Utilities Industry Spiros Potamitis,
Paul Malley		 source 8
SGF 2018 A Study of Modeling Approaches for Predicting Dropout in a Business College Helmut Schneider,
Xuan Wang		 source 8
SGF 2018 Accelerate your End-to-End Enterprise Decisions with SAS Viya David R. Duling,
Steve Sparano		 source 12
SGF 2018 Are New Modeling Techniques Worth It? Tom Zougas source 8
SGF 2018 Claim Analytics: A Litigation Prediction Case Study Mei Najim source 18
SGF 2018 Credit Score: A Comparison of Gradient Boosting with Logistic Regression in Practical Cases Paulo Di Cellio Dias,
Marc Witarsa		 source 25
SGF 2018 Do You Need to Put Your Data on a Diet? Howard Plemmons Jr.,
Priya Sharma		 source 7
SGF 2018 Examining the Drivers of Hospital Re-admission of Type-2 Diabetic patients Shashank Reddy Gudipati source 9
SGF 2018 Interpreting Black-Box Machine Learning Models Using Partial Dependence and Individual Conditional Expectation Plots Ray Wright source 19
SGF 2018 Make SAS Enterprise Miner Play Nicely with SAS Viya Beth Ebersole source 31
SGF 2018 Prediction and Interpretation for Machine Learning Regression Methods David Richard Cutler source 16
SGF 2018 Risk Pathways: Using Machine Learning Techniques of SAS Viya to Understand Customer Risk Drivers Leigh Ann Herhold source 14
SGF 2018 SAS Visual Investigator and SAS Visual Analytics: Bridging the Gap between Subject Matter Experts Emily Chapman-Mcquiston source 12
SGF 2018 SAS Viya : The Beauty of REST in Action Sean Ankenbruck,
Grace Heyne Lybrand		 source 7
SGF 2018 To Show or Not to Show? Using SAS Solutions to Maximize Patient Scheduling In Medical Clinics Mia Lyst,
Yijie Li		 source 8
SGF 2018 Top 10 Tips for SAS Enterprise Miner Based on 20 Years' Experience Melodie Rush source 21
SGF 2018 Using Predictive Analytics to Improve a Student Advising System Thanuja Sakruti,
Youyou Zheng		 source 13
SESUG 2017 Churn the Data Around - A Machine Learning Approach to Understanding Why Customers Leave Sean Ankenbruck source 9
SESUG 2017 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 25
SCSUG 2017 Analysis of the effects of financial parameters on GDP and poverty using panel data analysis. Akshay Arora source 13
SCSUG 2017 Analyzing Theft Occurrences in Chicago Using SAS Enterprise Miner 14.1 Shikha Prasad,
Kunal Parekh,
Goutam Chakraborty,
Miriam McGaugh		 source 10
SCSUG 2017 Enhancement of Clinical Decision Making Using Predictive Modeling Archana Chinnaswamy source 9
SCSUG 2017 Prediction of Used Cars? Prices by Using SAS EM Jaideep Muley,
Vijay Kumar Movva		 source 12
SCSUG 2017 Predictive Analysis for Classifying Type 2 Diabetes Patients Using SAS Enterprise Miner 14.1 and SAS Enterprise Guide 7.1 Saurabh Sanjayrao Kokad source 10
SCSUG 2017 Use Machine Learning to Discover Your Rules David R. Duling source 10
MWSUG 2017 Claim Analytics Mei Najim 18
WUSS 2017 A Data Mining Approach for Developing Intervention Programs to Lessen Body Dissatisfaction and Promote Healthy Weight Management Pitipa Chongwatpol,
Jongsawas Chongwatpol		 source 12
WUSS 2017 An Overview of SAS Visual Data Mining and Machine Learning on SAS Viya Radhikha Myneni source 23
WUSS 2017 Decision Trees: a Gentle Introduction Richard Hector source 11
SGF 2017 A Data Mining Approach to Predict Students at Risk Youyou Zheng,
Thanuja Sakruti		 source 13
SGF 2017 An Overview of SAS Visual Data Mining and Machine Learning on SAS Viya Jonathan Wexler,
Susan Haller		 source 23
SGF 2017 Applying Text Analytics and Machine Learning to Assess Consumer Financial Complaints Tom Sabo source 15
SGF 2017 Examining Higher Education Performance Metrics with SAS Enterprise Miner and SAS Visual Analytics Taylor Blaetz,
Tuesdi Helbig,
Gina Huff,
Matt T. Bogard		 source 15
SGF 2017 Interactive Modeling in SAS Visual Analytics Donald R. Chapman,
Jonathan Wexler		 source 16
SGF 2017 Modeling the Merchandise Return Behavior of Anonymous and Non-Anonymous Online Apparel Retail Shoppers Sunny Lam source 20
SGF 2017 Open Your Mind: Use Cases for SAS and Open-Source Analytics Tuba Islam source 10
SGF 2017 Outline Outliers: Adding a Business Sense Alex Glushkovsky source 17
SGF 2017 Predictive Accuracy: A Misleading Performance Measure for Highly Imbalanced Data Josephine Akosa source 12
SGF 2017 Property and Casualty Insurance Predictive Analytics in SAS Mei Najim source 17
SGF 2017 Random Forests with Approximate Bayesian Model Averaging Tiny Du Toit,
Andre De Waal		 source 11
SGF 2017 Real AdaBoost: Boosting for Credit Scorecards and Similarity to WOE Logistic Regression Paul Edwards source 12
SGF 2017 Sankey Diagram: A Compelling, Convenient, and Informational Path Analysis with SAS Visual Analytics Abhilasha Tiwari source 17
SGF 2017 SAS Macros for Binning Predictors with a Binary Target Bruce S. Lund source 13
SGF 2017 Text Mining of Movie Synopsis by SAS Enterprise Miner Yiyun Zhou source
pdf		 3
SGF 2017 The Effects of Socioeconomic, Demographic Variables on US Mortality Using SAS Visual Analytics Catherine Loveless-Schmitt source
pdf		 22
SGF 2017 The Three Amigos Factors: Determining Term Deposit Purchases: How a Bank Can Get Other People's Money Gina Colaianni,
Bogdan Gadidov,
Matthew Mitchell		 source 59
SGF 2017 Use Machine Learning to Discover Your Rules David R. Duling source 10
SGF 2017 Using Python with SAS Cloud Analytic Services Kevin D. Smith,
Xiangxiang Meng		 source 23
SGF 2017 Using SAS to Analyze Emergency Department Visits: Medicaid Patients Compared to Other Pay Sources Bradley Casselman,
Taylor K. Larkin,
Denise J. McManus		 source 16
SGF 2017 Using Segmentation to Build More Powerful Models with SAS Visual Analytics Darius S. Baer,
Sam Edgemon		 source 18
SGF 2017 What Statisticians Should Know about Machine Learning David Richard Cutler source 13
SCSUG 2016 Analysis of degradation patterns in the clinical efficacies of anti-microbial drug usage Shweta Arya,
Bhuvaneswari Yallabandi		 source 12
SCSUG 2016 Determining the functionality of Water Pumps in Tanzania Using SAS EM and VA Indra Kiran Chowdavarapu,
Vivek Damodaran Manikandan		 source 9
SCSUG 2016 Show Me the Money! Text Analytics for Decision-Making in Government Spending Tom Sabo source 13
SESUG 2016 A Data Mining Approach to Predict Student-at-risk Youyou Zheng,
Thanuja Sakruti,
Abhishek Uppalapati,
Sivakumar Jaganathan		 source 12
SESUG 2016 Know your Interest Rate Anirban Chakraborty,
Goutam Chakraborty		 source 16
SESUG 2016 Predicting student success based on interactions with virtual learning environment Vivek Doijode,
Neha Singh		 source 10
SESUG 2016 Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT Software Robert N. Rodriguez source 23
MWSUG 2016 Identifying the factors responsible for loan defaults and classification of customers using SAS Enterprise Miner Juhi Bhargava,
Prashanth Reddy Musuku		 13
MWSUG 2016 Property and Casualty Insurance Predictive Analytics in SAS Mei Najim 17
WUSS 2016 Social Media, Anonymity, and Fraud: HP Forest Node in SAS Enterprise Miner Taylor K. Larkin,
Denise J. McManus		 source 5
WUSS 2016 Statistical Model Building for Large, Complex Data: Four New Directions in SAS/STAT Software Robert N. Rodriguez source 23
SGF 2016 A Property and Casualty Insurance Predictive Modeling Process in SAS Mei Najim source 14
SGF 2016 Application of Data Mining Techniques in Improving Breast Cancer Diagnosis Josephine Akosa source
presentation		 10
SGF 2016 Application of Gradient Boosting through SAS Enterprise Miner to Classify Human Activities Minh Pham,
Mary Ruppert-Stroescu,
Mostakim Tanjil		 source
presentation		 8
SGF 2016 Arrest Prediction and Analysis based on a Data Mining Approach Karan Rudra,
Goutam Chakraborty,
Maitreya Kadiyala		 source 9
SGF 2016 Building a Recommender System with SAS to Improve Cross-Selling for Online Retailers Miao Nie,
Shanshan Cong		 source
zip		 12
SGF 2016 Classifying Fatal Automobile Accidents in the US, 2010-2013: Using SAS Enterprise Miner to Understand and Reduce Fatalities Catherine LaChapelle,
Daniel Brannock,
Aric LaBarr,
Craig Shaver		 source 11
SGF 2016 Credit Card Interest and Transactional Income Prediction with an Account-Level Transition Panel Data Model Using SAS/STAT and SAS/ETS Software Denys Osipenko source 20
SGF 2016 Debt Collection through the Lens of SAS Analytics Karush Jaggi,
Harold Dickerson,
Thomas Waldschmidt		 source
presentation		 11
SGF 2016 Diagnosing Obstructive Sleep Apnea: Using Predictive Analytics Based on Wavelet Analysis in SAS/IML Software and Spectral Analysis in PROC SPECTRA Woranat Wongdhamma source 12
SGF 2016 Enhanced Segmentation Using SAS Visual Analytics and SAS Visual Statistics Darius S. Baer,
Suneel Grover		 source 19
SGF 2016 Ensemble Modeling: Recent Advances and Applications Wendy Czika,
Ye Liu		 source 20
SGF 2016 Extending the Armed Conflict Location & Event Data Project with SAS Contextual Analysis Tom Sabo source 14
SGF 2016 From Sensors to Solutions: An Example of Analytics in Motion Milad Falahi,
Gilbert Hernandez		 source 12
SGF 2016 Keeping Hope Afloat: How to Prevent Financial Loss amongst a Sea of Online Pirates Sam Atassi,
Jamie Hutton		 source 15
SGF 2016 Lyric Complexity and Song Popularity: Analysis of Lyric Composition and Relation among Billboard Top 100 Songs John Harden,
Yang Gao,
Vojtech Hrdinka,
Chris Linn		 source 15
SGF 2016 Making Better Decisions about Risk Classification Using Decision Trees in SAS Visual Analytics Stephen M. Overton,
Ben Murphy		 source 13
SGF 2016 Mass-Scale, Automated Machine Learning and Model Deployment Using SAS Factory Miner and SAS Decision Manager Jonathan Wexler,
Steve Sparano		 source 19
SGF 2016 Personal Lending: Customer Credit and Pricing Optimization Yuri Medvedev source 19
SGF 2016 Predicting Human Activity Sensor Data Using an Auto Neural Model with Stepwise Logistic Regression Inputs Venkata Vennelakanti source
presentation		 10
SGF 2016 Predicting If Mental Health Facilities Will Offer Free Treatment to Patients Who Cannot Afford It Ram Poudel,
Lynn Xiang		 source 11
SGF 2016 Predicting Occurrence Rate of Systemic Lupus Erythematosus and Rheumatoid Arthritis in Pregnant Women Ravikrishna Vijaya Kumar,
Shrie Raam Sathyanarayanan		 source 15
SGF 2016 Predicting Rare Events Using Specialized Sampling Techniques in SAS Rhupesh Damodaran Ganesh Kumar,
Kiren Raj Mohan Jagan Mohan		 source 7
SGF 2016 Predicting the Current Market Value of a Housing Unit across the Four Census Regions of the United States Using SAS Enterprise Miner 12.3 Mostakim Tanjil,
Goutam Chakraborty		 source
presentation		 12
SGF 2016 Reducing and Screening Redundant Variables in Logistic Regression Models Using SAS/STAT Software and SAS Enterprise Miner Xinghe Lu source 10
SGF 2016 SAS Visual Statistics 8.1: The New Self-Service, Easy Analytics Experience Xiangxiang Meng,
Donald R. Chapman,
Cheryl LeSaint		 source 11
SGF 2016 Statistical Model Building for Large, Complex Data: Five New Directions in SAS/STAT Software Bob Rodriguez source 23
SGF 2016 Streaming Decisions: How SAS Puts Streaming Data to Work Fiona McNeill,
David R. Duling,
Steve Sparano		 source
zip		 15
SGF 2016 Taming the Rule Charlotte Crain,
Chris Upton		 source 13
MWSUG 2015 A Property & Casualty Insurance Predictive Modeling Process in SAS Mei Najim 14
MWSUG 2015 Debt Collection Through SAS Analytics Lens Karush Jaggi,
Thomas Waldschmidt,
Harold Dickerson,
Eric Hayes,
Goutam Chakraborty		 11
MWSUG 2015 Get the highest bangs for your marketing bucks using Incremental Response Models in SAS Enterprise Miner Delali Agbenyegah 8
PHUSE EU 2015 Is R the Right Tool for Me? [presentation] Peter Bewerunge source 23
PHUSE EU 2015 SAS Software Demonstration - SAS In-Memory Visual Analytics [presentation] Andy Bayliss source 24
SESUG 2015 Predictive Modeling Using SAS Visual Statistics: Beyond the Prediction Xiangiang Meng,
Wayne Thompson,
Jennifer Ames		 source 12
WUSS 2015 Application of Data Mining in Energy Industry: A Case Study of NOx Prediction Jongsawas Chongwatpol source 9
WUSS 2015 SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data Maura E. Stokes source 25
PharmaSUG 2015 How to Harness Your Company-s Wiki for World Domination (or - Even Better - to Write the Best Reusable Code Possible) Kurtis Cowman source 8
PharmaSUG 2015 Proper Parenting: A Guide in Using ADaM Flag/Criterion Variables and When to Create a Child Dataset Richann J. Watson,
Karl Miller,
Paul K. Slagle		 source 10
SGF 2015 Applied Analytics in Festival Tourism: A Case Study of Intention-to-Revisit Prediction in an Annual Local Food Festival in Thailand Jongsawas Chongwatpol,
Thanathorn Vajirakachorn		 source 13
SGF 2015 Credit Card Holders' Behavior Modeling: Transition Probability Prediction with Multinomial and Conditional Logistic Regression in SAS/STAT Denys Osipenko,
Jonathan Crook		 source 13
SGF 2015 Determining the Key Success Factors for Hit Songs in the Billboard Music Charts Piboon Banpotsakun,
Jongsawas Chongwatpol		 source 12
SGF 2015 Discovering Personality Type through Text Mining in SAS Enterprise Miner 12.3 [presentation] Mark L. Schneider,
Andrew Van Der Werff		 source 7
SGF 2015 Donor Sentiment and Characteristic Analysis Using SAS Enterprise Miner and SAS Sentiment Analysis Studio Ramcharan Kakarla,
Goutam Chakraborty		 source 12
SGF 2015 Educating Future Business Leaders in the Era of Big Data Tonya E. Balan source 8
SGF 2015 Killing Them with Kindness: Policies Not Based on Data Might Do More Harm Than Good Tuesdi Helbig,
Matthew Foraker		 source 22
SGF 2015 Modeling to Improve the Customer Unit Target Selection for Inspections of Commercial Losses in the Brazilian Electric Sector: The case of CEMIG Sergio Henrique Ribeiro,
Iguatinan Monteiro		 source 7
SGF 2015 Predicting Readmission of Diabetic Patients Using the High-Performance Support Vector Machine Algorithm of SAS Enterprise Miner 13.1 Hephzibah Munnangi,
Goutam Chakraborty		 source 10
SGF 2015 Predicting Transformer Lifetime Using Survival Analysis and Modeling Risk Associated with Overloaded Transformers Using SAS Enterprise Miner 12.1 Balamurugan Mohan,
Goutam Chakraborty		 source 18
SGF 2015 Predictive Modeling Using SAS Visual Statistics: Beyond the Prediction Xiangxiang Meng,
Jennifer Ames,
Wayne Thompson		 source 12
SGF 2015 SAS Visual Analytics for Fun and Profit: A College Football Case Study John Davis source 18
SGF 2015 SAS/STAT 14.1: Methods for Massive, Missing, or Multifaceted Data Maura E. Stokes,
Bob Rodriguez		 source 25
SGF 2015 Show Me the Money! Text Analytics for Decision-Making in Government Spending Tom Sabo source 13
SGF 2015 Take a Bite Out of Crime with SAS Visual Scenario Designer Yue Qi source 10
SGF 2015 Understanding Characteristics of Insider Threats by Using Feature Extraction Ila Gokarn,
Clifton Phua		 source 14
SGF 2015 Using SAS to Deliver Web Content Personalization Using Cloud-Based Clickstream Data and On-premises Customer Data Mahesh Subramanian,
Suneel Grover		 source 24
SGF 2015 Want an Early Picture of the Data Quality Status of Your Analysis Data? SAS Visual Analytics Shows You How Gerhard Svolba source
zip		 19
SESUG 2014 Dashboards with SAS Visual Analytics Patricia S. Aanderud,
Michelle Homes		 source 20
SESUG 2014 Text Analytics using High Performance SAS Text Miner Edward R. Jones source 7
MWSUG 2014 Text Analytics in High Performance SAS and SAS Enterprise Miner Edward R. Jones 16
PharmaSUG CN 2014 From Coal Mining to Data Mining: Advancing Programming Management for Clinical Projects with Text Analytics Zhouming Sun 10
WUSS 2014 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 8
SGF 2014 An Analytical Approach for Bot Cheating Detection in a Massive Multiplayer Online Racing Game [presentation] Andrea Villanes source 10
SGF 2014 Big Digital Data, Analytic Visualization, and the Opportunity of Digital Intelligence Suneel Grover source 17
SGF 2014 Building Gamer Segmentation in the Credit Card Industry Using SAS Enterprise Guide Yang Ge source 10
SGF 2014 Clustering and Predictive Modeling of Patient Discharge Records with SAS Enterprise Miner Linda Schumacher,
Goutam Chakraborty		 source 9
SGF 2014 Customer Perception and Reality: Unraveling the Energy Customer Equation Mark Konya,
Kathy Ball		 source 11
SGF 2014 How to Interpret SVD Units in Predictive Models? Murali Krishna Pagolu,
Goutam Chakraborty		 source 10
SGF 2014 Improving the Thermal Efficiency of Coal-Fired Power Plants: A Data Mining Approach Thanrawee Phurithititanapong,
Jongsawas Chongwatpol		 source 12
SGF 2014 Internet Gambling Behavioral Markers: Using the Power of SAS Enterprise Miner 12.1 to Predict High-Risk Internet Gamblers Sai Vijay Kishore Movva,
Vandana Reddy,
Goutam Chakraborty		 source 11
SGF 2014 Model Variable Selection Using Bootstrap Decision Tree David J. Corliss source 7
SGF 2014 Prediction of the Rise in Sea Level by the Memory-Based Reasoning Model Using SAS Enterprise Miner 12.1 [presentation] Prasanna K S Sailaja Bhamidi,
Goutam Chakraborty		 source 4
SGF 2014 Reevaluating Policy and Claims Analytics: A Case of Corporate Fleet and Non-Fleet Customers in the Automobile Insurance Industry Kittipong Trongsawad,
Jongsawas Chongwatpol		 source 10
SGF 2014 Researching Individual Credit Rating Models Colin Nugteren source 12
SGF 2014 SAS Admins Need a Dashboard, Too Patricia S. Aanderud,
Michelle Homes		 source 20
SGF 2014 Text Mining Reveals the Secret of Success: Identification of Sales Determinants Hidden in Customers' Opinions Rafal Wojdan source 18
SGF 2014 The Role of Customer Response Models in Customer Solicitation Center's Direct Marketing Campaign Arun Mandapaka,
Amit Kushwah,
Goutam Chakraborty		 source 12
SGF 2014 The Soccer Oracle: Predicting Soccer Game Outcomes Using SAS Enterprise Miner [presentation] Vandana Reddy,
Sai Vijay Kishore Movva		 source 3
SGF 2014 The Use of Analytics for Insurance Claim Fraud Detection: A Unique Challenge Roosevelt Mosley,
Nick Kucera		 source 15
SGF 2014 Using SAS Enterprise Miner to Predict the Injury Risk Involved in Car Accidents Prateek Khare,
Vandana Reddy,
Goutam Chakraborty		 source 7
WUSS 2013 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 8
SESUG 2013 Analytical Approach for Bot Cheating Detection in a Massive Multiplayer Online Racing Game Andrea Villanes source 10
SESUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SESUG 2013 Using JMP Partition to Grow Decision Trees in Base SAS Mira Shapiro source 16
MWSUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey 16
NESUG 2013 Model Variable Selection Using Bootstrapped Decision Tree David J. Corliss 8
SGF 2013 A Data-Driven Analytic Strategy for Increasing Yield and Retention at Western Kentucky University Using SAS Enterprise BI and SAS Enterprise Miner Matt T. Bogard source 12
SGF 2013 Commuting Time and Accessibility in a Joint Residential Location, Workplace, and Job Type Choice Model Ignacio A. Inoa,
Nathalie Picard,
André de Palma		 source 13
SGF 2013 Detecting Cross-Channel Fraud Using SAS Krutharth Kumar Peravalli Venkata Naga,
Srikar Rayabaram		 source 9
SGF 2013 Estimates of Personal Revenue from Credit and Sociodemographic Information Combining Decision Trees and Artificial Neural Networks (ANN) Deybis Florez Hormiga source 4
SGF 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SGF 2013 High Performance Statistical Modeling Bob Rodriguez,
Robert A. Cohen		 source 19
SGF 2013 Investigating the Impact of Amazon Kindle Fire HD 7? on Amazon.com Consumers Using SAS Text Miner and SAS Sentiment Analysis View Paper View Poster Goutam Chakraborty,
Hari Hara Sudhan Duraidhayalu,
Srihari Nagarajan		 source
pdf		 14
SGF 2013 Predicting Women's Department Purchases in a Retail Store By Using the SEMMA Methodology Michael Soto source 12
SGF 2013 Predictive Modeling in Sports Leagues: An Application in the Indian Premier League Goutam Chakraborty,
Pankush Kalgotra,
Ramesh Sharda		 source 10
SGF 2013 The Forest and the Trees: See It All with SAS Visual Analytics Explorer Nascif Abousalh-Neto source 14
SGF 2013 Using Classification and Regression Trees (CART) in SAS Enterprise Miner? for Applications in Public Health Leonard Gordon source 8
SGF 2013 Using the Boosting Technique to Improve the Predictive Power of a Credit Risk Model Alejandro Correa Bahnsen,
Andres F. Gonzalez,
Darwin A. Amezquita		 source 7
NESUG 2012 An Animated Guide: Regression Trees in JMP and Enterprise Miner Russell M. Lavery 32
MWSUG 2012 An Analysis of Diabetes Risk Factors Using Data Mining Approach Akkarapol Sa-ngasoongsong,
Jongsawas Chongwatpol		 11
MWSUG 2012 Applying Analytics to High Performance Customer Profitability Models in Financial Services Tony Adkins,
Gary Cokins		 9
MWSUG 2012 JMP Pro Bootstrap Forest George J. Hurley 10
MWSUG 2012 Methods for Interaction Detection in Predictive Modeling Using SAS Douglas Thompson 13
PharmaSUG 2012 Making Your SAS Data JMP Through Hoops Mira Shapiro source 19
PharmaSUG 2012 Using JMP Partition to Grow Decision Trees in Base SAS Mira Shapiro source 16
SGF 2012 An Experimental Comparison of Classification Techniques for Imbalanced Credit Scoring Data Sets Using SAS Enterprise Miner Iain L. Brown source 14
SGF 2012 Applying Analytics to High Performance Customer Profitability Models in Financial Services Tony Adkins,
Gary Cokins		 source 9
SGF 2012 Building WOE Binned LGD Scorecards using SAS Enterprise Miner Anthony J. van Berkel,
Naeem Siddiqi		 source 14
SGF 2012 CSI: Customer Segmentation Intelligence for Increasing Profits Darius S. Baer source 13
SGF 2012 Developing a Predictive Model for Customer Trip Purpose to Be Integrated into Enterprise Strategy and Analytics Jonathan Levine source 16
SGF 2012 Kass Adjustments in Decision Trees on Binary/Interval Target Manoj K. Immadi source 9
SGF 2012 Leveraging Analytics in Transportation to Create Business Value Vijitha Kaduwela source 12
SGF 2012 Making Your SAS Data JMP Through Hoops Mira Shapiro source 19
SGF 2012 Using SAS Enterprise BI and SAS Enterprise Miner to Reduce Student Attrition Matt T. Bogard,
Chris James,
Tuesdi Helbig,
Gina Huff		 source 10
SCSUG 2011 Kass Adjustments in Decision Trees on Binary/Interval Target Variable Manoj Immadi source 10
SCSUG 2011 Prediction on Diabetes Using Data Mining Approach Pardha Repalli source 10
WUSS 2011 ChiD, A Chi-2 - Based Discretization Algorithm Ross Bettinger source 9
PHUSE EU 2011 Introduction of Pharmaco-economics for non-health economists Elhem Sbaa source
presentation source		 4
MWSUG 2011 What Are People Saying about Your Company, Your Products, or Your Brand? Kathy Lange,
Saratendu Sethi		 16
NESUG 2011 An Optimal Search Process of "Eigen Knots" for Spline Logistic Regression John Gao,
Cheryl Caswell		 7
NESUG 2011 Feature Selection and Dimension Reduction Techniques in SAS Sassoon Kosian,
Varun Aggarwal		 6
PharmaSUG 2011 Clinical Trials Versus Health Outcomes Research: SAS/STAT Versus SAS Enterprise Miner Patricia B. Cerrito source 15
PharmaSUG 2011 Effectiveness Of Disease Management Care In The Case Of Heart Failure Beatrice Ugiliweneza source 11
SGF 2011 Data Mining in SAS with Open-Source Software Zhengping Ma source 11
SGF 2011 Data Mining Using JMP Murphy Choy source 9
SGF 2011 JMP 9 and Interactive Statistical Discovery John P. Sall source 15
SGF 2011 Patron Analytics in the Casino and Gaming Industry: How the House Always Wins Scott W. Sutton source 7
SGF 2011 Predictive Analysis of Auto Insurance Purchasing Behavior on the Internet Roosevelt Mosley source 15
SGF 2011 Ratemaking Using SAS Enterprise Miner: An Application Study Billie Anderson source 20
SGF 2011 Taking Disease and Health Management Analytics into the Next Generation George S. Habek source 13
SGF 2011 The Anti-Curse: Creating an Extension to SAS Enterprise Miner Using PROC ARBORETUM Andrew S. Cathie source 11
SGF 2011 What Are People Saying about Your Company, Your Products, or Your Brand? Kathy Lange,
Saratendu Sethi		 source 16
WUSS 2010 A New and Simpler Way to Compute Body's "Maximum Weight Limit" George C. J. Fernandez source 12
WUSS 2010 Data Visualization: "Every Picture Tells a Story" or "Putting Atomic Numbers on Your Socks"? AnnMaria De Mars source 11
WUSS 2010 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 7
MWSUG 2010 Evaluation of Methods to Determine Optimal Cut Points for Predicting Mortgage Default Valentin Todorov,
Douglas Thompson		 11
MWSUG 2010 To Investigate the Impact of Medicare Part D on the Cost Effectiveness of Diabetes Medications and Health Outcomes with SAS Xiao Wang 8
SGF 2010 An Analytical Approach to Determining Customer Value in the Property and Casualty Insurance Industry Roosevelt Mosley source 20
SGF 2010 BMI Made Simple: What Is Your "Maximum Weight Limit? George C. J. Fernandez source 12
SGF 2010 Building a Decision Tree from Decision Stumps Murphy Choy,
Peter L. Flom		 source 7
SGF 2010 Data and Text Mining in SAS Warranty Analysis 4.2 Ned Maran,
Wei Huang		 source 13
SGF 2010 Rapid Predictive Modeling for Customer Intelligence Wayne Thompson,
David R. Duling		 source 12
SGF 2010 The Power of the Group Processing Facility in SAS Enterprise Miner Sascha Schubert source 13
MWSUG 2009 A Comparison of Decision Tree and Logistic Regression Model Xianzhe Chen 10
MWSUG 2009 Demonstration of Organic Growth Modeling for B to B Marketing Karen Ziton 15
MWSUG 2009 Outcome Research for Diabetic Inpatients with SAS Enterprise Miner 5.2 Xiao Wang 21
MWSUG 2009 Predictive Modeling in Enterprise Miner Versus Regression Patricia B. Cerrito 27
NESUG 2009 Successfully Implementing Predictive Analytics in Direct Marketing John Blackwell,
Tracy DeCanio		 7
SGF 2009 Generalizations of Generalized Additive Model (GAM): A Case of Credit Risk Modeling Wensui Liu,
Jimmy Cela,
Chuck Vu		 source 14
SGF 2009 The Next Generation: SAS Enterprise Miner 6.1 David R. Duling,
Wayne Thompson		 source 10
SGF 2009 The Problem of Regression Assumptions and the Use of Predictive Modeling Patricia B. Cerrito source 20
SESUG 2008 Reject Inference Methodologies in Credit Risk Modeling Derek Montrichard source 10
SESUG 2008 SAS Hash Objects: An Efficient Table Look-Up in the Decision Tree Ying Liu source 15
PHUSE EU 2008 Today's Project Management Software: It's Easier Thank You Think! Jenny Gandhi source 10
MWSUG 2008 The Difference Between Predictive Modeling and Regression Patricia B. Cerrito 19
SGF 2008 Data Mining to Predict the Occurrence of Resistant Infection Patricia B. Cerrito source 20
SGF 2008 Identifying Potential Default Loan Applicants: A Case Study of Consumer Credit Decision for Chinese Commercial Bank Zhangxi Lin,
Qiwei Gan,
Binjie Luo		 source 12
SGF 2008 In Search for a Golden Algorithm Tamara S. Slipchenko,
Candice Bowman,
Catherine Sugar,
Allen L. Gifford		 source 9
SGF 2008 It's 9:00 AM: Do You Know Where Your Critical Talent Is? Retention Analytics for Human Capital Management Lynn Creecy,
Bradley W. Klenz		 source 11
SGF 2008 New Strategies for Identifying Customer Usage Patterns Barry deVille source 9
SGF 2008 Understanding Your Customer: Segmentation Techniques for Gaining Customer Insight and Predicting Risk in the Telecom Industry Glendon Cross,
Wayne Thompson		 source 14
SGF 2008 Using SAS Enterprise Miner to Prescribe a Pre-Screen Mailing Rex Pruitt source 6
NESUG 2007 A SAS Constellation Diagram Has Many Faces Shi-Tao Yeh pdf 17
NESUG 2007 Variable Selection and Variable Transformations in SAS Enterprise Miner 5.2 Kattamuri S. Sarma 12
SESUG 2007 Data Mining Episode Groupers Patricia B. Cerrito source 13
SESUG 2007 SAS Formats, More Than Just Another Pretty Face Ying Liu source 15
MWSUG 2007 Analyzing Survey Data Using Decision Trees Morgan C. Wang 25
MWSUG 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga 20
MWSUG 2007 Using Data Mining Techniques to Predict Student Development and Retention Morgan C. Wang 59
WUSS 2007 Case Study: Development of an HIV casefinding algorithm with SAS Enterprise Miner Tamara Slipchenko,
Candice Bowman,
Yuexin (Cindy) Chen,
Catherine Sugar,
Allen L. Gifford		 source 9
WUSS 2007 Data Mining Using SAS Enterprise Miner Randall Matignon source 10
SCSUG 2007 Deploying Predictive Models in the Newspaper Industry April Wilson,
Kuao-Tien Chen		 23
SGF 2007 Critical Success Factors for Rate Making with SAS Enterprise Miner Hrushikesh Khopkar,
Jay King		 source 17
SGF 2007 Find the Best Prospects for a New Product by Using a Data Mining Model Ting Millette source 8
SGF 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga source 20
SGF 2007 Predictive Modeling in Higher Education Tom Bohannon source 14
SGF 2007 SAS Constellation Diagram Has Many Faces Shi-Tao Yeh source 16
SCSUG 2006 Data Mining at the Texas State Auditor's Office Thomas J. Winn Jr. 11
SCSUG 2006 What's New in SAS Enterprise Miner 5.2 Wayne Thompson,
David R. Duling		 10
SESUG 2006 Predictive Modeling to Analyze Hospital Charges Versus Reimbursements Chakib Battioui source 12
WUSS 2006 Enterprise Guide for Business Analysts Sunil Kumar Gupta source 10
WUSS 2006 Find the Best Prospects for a New Product by Using a Data Mining Model Ting Wu source 8
NESUG 2006 Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 Jodi Blomberg,
Jacqueline K. Long		 12
SUGI 2006 Fraud Detection - A Primer for SAS Programmers Thomas J. Winn Jr. source 6
SUGI 2006 Predicting Child Support Payment Delinquency Using SAS Enterprise Miner 5.1 Jodi Blomberg,
Jacqueline K. Long		 source 12
SUGI 2006 Text Mining with "Holographic" Decision Tree Ensembles Barry deVille source 7
SUGI 2006 What's New in SAS Enterprise Miner 5.2 Wayne Thompson,
David R. Duling		 source 10
PHUSE EU 2005 Data Mining in a Pharmaceutical Environment Franky De Cooman source 4
MWSUG 2005 Comparison Of Enterprise Miner And SAS/STAT For Data Mining Patricia B. Cerrito 12
MWSUG 2005 Information Discovery Using Decision Trees Morgan C. Wang 79
MWSUG 2005 Mining Transactional And Time Series Data Michael J. Leonard 26
WUSS 2005 Enterprise Guide for Business Analysts Sunil Kumar Gupta source 13
SUGI 2005 Combining Decision Trees with Regression in Predictive Modeling with SAS Enterprise Miner Kattamuri S. Sarma source 10
SUGI 2005 Decision Tree Validation: A Comprehensive Approach Sylvain Tremblay source 8
SUGI 2005 Mining Transactional And Time Series Data Michael J. Leonard,
Brenda Wolfe		 source 26
NESUG 2004 Using SAS at SAS: The Mining of SAS Technical Support Annette M. Sanders,
Craig DeVault		 22
SCSUG 2004 Data Mining and the Use of SAS to Deploy Scoring Rules Neil S. Fleming 13
SCSUG 2004 Fraud Detection - A Primer for SAS Programmers Thomas J. Winn Jr. 9
SESUG 2004 Using SAS at SAS: The Mining of SAS Technical Support Annette M. Sanders,
Craig DeVault		 source 22
WUSS 2004 Analysis and Reporting Made Easier using Enterprise Guide Sunil Kumar Gupta source 7
MWSUG 2004 Using SAS at SAS: The timing of SAS Tech Support Annette M. Sanders,
Craig DeVault		 22
SUGI 2004 Using SAS at SAS: The Mining of SAS Technical Support Annette M. Sanders,
Craig DeVault		 source 23
SESUG 2003 Identifying Person Duplicates of Short Geographic Distance by Computer Matching Thomas Mule source 10
SEUGI 2003 A Simplified Customer Analysis System for Millions of Telecom Customers Leveraging Analytical SAS Software [presentation] Tomoko Shibata source 26
SEUGI 2003 Analytical CRM at Swisscom Fixnet - The data warehouse concept, mode development with Enterprise Miner and implementation [presentation] Miltiadis Sarakinos source 22
SEUGI 2003 Customer Insight development in Vodafone Italy [presentation] Emanuele Baruffa source 23
SEUGI 2003 Data Mining on an IMS Data Base of Schizophrenic Patients: Assessing Unmet Need and Costs [presentation] Franky De Cooman,
G. Nuyts		 source 17
SEUGI 2003 Developing an Optimal Product Offering Strategy and Maximizing Overall Profitablility of Current Clients [presentation] Tamer Keshi source 13
SEUGI 2003 New Directions in SAS Enterprise Miner for SAS 9.1 [presentation] David R. Duling,
Sascha Schubert		 source 26
SEUGI 2003 Predicting churn behaviour for Optimus [presentation] Ricardo Almedia source 20
VIEWS 2003 Customer churn - An operational comparison of logistic regression, decision tree & neural network models. Arun Parekkat 4
SUGI 2003 Monitoring, Analyzing, and Optimizing Waterflood Responses Leon L. Fedenczuk source 5
SUGI 2003 Multistage Cross-Sell Model of Employers in the Financial Industry Kwan Park,
Steve Donohue		 source 5
SCSUG 2002 Statistical Pattere Recognition Using Enterprise Miner and Self-Organizing Maps Keith A. Jones 8
SEUGI 2002 Bankruptcy scoring using the SAS Enterprise Miner [presentation] Michael Wetzel source 18
SEUGI 2002 Buidling Credit Scorecards using SAS Enterprise Miner [presentation] John Lawrence,
Martin Crossley		 source 11
SEUGI 2002 Data Mining experiences in predicting TLC Churn [presentation] Marco Richeldi source 20
SEUGI 2002 Improving Bank Profits with Next-Generation Data Mining Techniques [presentation] Rafael Alverez Cuesta source 17
SEUGI 2002 SAS Enterpise Miner: What does the future hold? [presentation] David R. Duling,
Sascha Schubert		 source 45
SUGI 2002 Algorithmic Answers for a Dance School Dilemma Wendy B. Dickinson source 5
SUGI 2002 To Neural or Not to Neural? - This Is the Question Leon L. Fedenczuk source 6
SUGI 2002 Tree-based Models: Identification of Influential Factors under Condition of Instability Pavel Brusilovskiy,
Yillian Yuan		 source 6
SUGI 2002 Using SAS Enterprise Miner for Data Quality Monitoring in the Veterans Health Administration's External Peer Review Program James H. Forsythe source 5
VIEWS 2001 Data Mining and Statistical Models in Marketing Campaigns of BT Retail Francesco Vivarelli,
Martyn Johnson		 9
VIEWS 2001 Knowledge Discovery and Data Mining Applied to Engineering Applications [presentation] Shirley Williams 22
WUSS 2001 Intelligent Agents and Applications in Enterprise Computing Anthony M. Dymond source 7
WUSS 2001 Using SAS Enterprise Miner for Forecasting Response and Risk Kattamuri S. Sarma source 10
SEUGI 2001 A retrospective evaluation of a data mining approach to fetal asphyxia at delivery in a hospital database [presentation] Olavi Kauhanen,
Seppo Heinonen		 source 53
SEUGI 2001 Building a compelling case for Enterprise Miner Within The Bank of Scotland [presentation] Simon Hughes source 33
SEUGI 2001 Data Mining In a Zero Latency Enterprise [presentation] Philip Bosinoff source 36
SEUGI 2001 Knowledge Solution for Credit Scoring [presentation] Henrik Wagner source 26
SEUGI 2001 SAS and CFMS Integration - Attacking Fraud in Next Generation Networks [presentation] Augusto Argento source 35
SEUGI 2001 Send in the Clones [presentation] Philip Whittall source 22
SEUGI 2001 WebMining [presentation] Goncalo Abreu,
Pedro Marques		 source 15
SUGI 2001 A Practical Introduction to the Power of Enterprise Miner Michael S. Lajiness source 7
SUGI 2001 Predictive Modeling in the Insurance Industry Using SAS Terry J. Woodfield source 5
SESUG 2000 Emerging Technologies Roadmap A Decision Tree Guide to Understanding SAS Strengths Gregory S. Barnes Nelson source 9
WUSS 2000 An Object-Oriented Expert System for the SAS Environment Anthony M. Dymond source 5
SEUGI 2000 Analysing the footprints of your customer - A case study by ask|net and SAS [presentation] Klaus-Peter Huber source 40
SEUGI 2000 Business Intelligence in Telefonica I+D (R&D) [presentation] Alfredo Jesus Serrano source 32
SEUGI 2000 Credit Scoring with Enterprise Miner [presentation] Henrik Wagner source 29
SEUGI 2000 Data Mining for Building & Not Digging [presentation] Kathryn Burn-Thornton source 22
SEUGI 2000 Enterprise Mineer vs Underlying SAS Code: A Performance Comparison [presentation] Usama Hasan source 11
SEUGI 2000 Genetic Data Analysis with Enterprise Mineer [presentation] John C. Brocklebank,
Wayne Thompson		 source 24
SEUGI 2000 Mining in Melodies [presentation] Bulcsu Fajszi,
Laszlo Surjan		 source 19
SEUGI 2000 The Customer Life-Time-Value in the Insurance-Industry [presentation] Gunter Schmolz source 16
SEUGI 2000 Using Enterprise Miner to explore pattern and process in biodiversity surveillance data for Great Britain [presentation] John W. Watkins,
Simon M. Smart		 source 11
PharmaSUG 2000 Data Mining and Statistics in a Pharmaceutical Environment Franky De Cooman 3
SUGI 2000 Data Warehousing for Manufacturing Yield Improvement Robert A. Rutledge source 10
SUGI 2000 Riding the Information Wave to Marketing Success: Web Enabled On-Line Analytical Processing from Your Data Warehouse George Bukhbinder,
Peter Babigian		 source 6
SUGI 2000 Using Enterprise Miner to Explore and Exploit Drug Discovery Data Michael S. Lajiness source 8
SEUGI 1999 Customer relationship management: organise for maximum ROI (Return on Information) Lynette Stassen source 13
SEUGI 1999 Data mining methodoligies for business: cross selling [presentation] Henrik Wagner source 37
SEUGI 1999 Integrating management reporting with SAS Software: balanced scorecard, data mining and OLAP Analysis for an insurance company [presentation] Patrick Imark source 30
SEUGI 1999 New product marketing analysis and launch [presentation] Jose Manuel Rey source 80
SEUGI 1999 Quality assurance and SAS Application Development B. Dudink,
A. Geerts,
I. König,
M. Klijn,
E. Lekkerkerker-Smit		 source 8
SUGI 1999 Use of Enterprise Miner and Multivariate Statistical Analysis to Build Fraud-Detection Models Shiao-Ping Lu source 5
WUSS 1998 Use of Data Enterprise Miner & Multivariate Statistical Analysis to Build Fraud-Detection Models Shiao-Ping Lu source 7
SESUG 1998 The SAS Travel Companion C. Olivia Parr Rud 1
PNWSUG 1998 Decision Tree Classification in Direct Marketing Robert Mengis 9
SEUGI 1998 Knowledge Discovery and Data Mining on the Example of Clinical Databases Leon Bobrowski,
Magdalena Topczewska		 source 6
SEUGI 1998 Time to market reduction: A methodological approach to the virual prototyping of stamped component F. Placidi,
Franca Vicino,
S. Martire		 source 13
SUGI 1998 Finding the Solution to Data Mining: A Map of the Features and Components of SAS Enterprise Miner Software Table of Contents John C. Brocklebank,
Mark Brown		 source 24
SUGI 1998 Mining the Data Mart: A Case Study with Stock Market Data James A. Cox,
Tonya L. Etchison		 source 11
SUGI 1998 Strategic Use of the SAS System in Banking Laurie Rose source 5
WUSS 1997 Some Applications of Data Mining Tools in Database Marketing Jiamin Liu source 6
NESUG 1997 Digging For Gold: Business Usage for Data Mining Kimberly A. Foster 6
NESUG 1997 Mining Your Data for Health Care Quality Improvement Greg Rogers 7
SEUGI 1997 Data Mining and SAS/SPECTRAVIEW software: a case study Annie Postic,
Bengt Bengtsson		 source 36
SEUGI 1997 Segmentation using decision trees Gerhard Held source 52
SUGI 1997 Mining Your Data for Health Care Quality Improvement Greg Rogers,
Ellen Joyner		 source 7
SEUGI 1996 Tree-based modelling with the SAS System Nick Dunkerton source 12
SEUGI 1996 TREEDISC - a method for identifying household segments Sten Sture source 11
NESUG 1990 Parsing a Compound Boolean Condition to Evaluate Its Clauses Individually and in Logical Groups Daniel M. Himmel 9
SUGI 1989 Statistical Experts Systems in SAS Software Pan-Yu Lai source 8

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