Services: Data Mining Project Assessment, Data Preparation For Data Mining, Data Mining Model Development, Data Mining Model Deployment, Data Mining Course: Overview for Project Managers, Data Mining Course: Overview for Practitioners, Customized Data Mining Engagements
Insight 1: Find Correlated Variables Prior to Modeling Topic: Data Understanding and Data Preparation Sub-Topic: Feature Selection Insight 2: Beware of Outliers in Computing Correlations Topic: Data Preparation Sub-Topic: Outliers Insight 3: Create Three Sampled Data Sets, not Two Topic: Modeling Sub-Topic: Sampling Insight 4: Use Priors to Balance Class Counts Topic: Modeling Sub-Topic: Decision Trees Insight 5: Beware of Automatic Handling of Categorical Variables Topic: Data Understanding and Data Preparation Sub-Topic: Feature Selection and Creation Insight 6: Gain Insights by Building Models from Several Algorithms Topic: Modeling Sub-Topic: Algorithm Selection Insight 7: Beware of Being Fooled with Model Performance Topic: Data Evaluation Sub-Topic: Model Performance
Client List and Case Studies
Upcoming Data Mining Seminars A Practical Introduction to Data Mining Upcoming courses (nationwide) Data Mining Level II: A drill-down of the data mining process, techniques, and applications Data Mining Level III: A hands-on day of data mining using real data and real data mining software Anytime Courses Overview for Project Managers: Train project managers on the data mining process. Overview for Practitioners: Train practitioners (data analysts, project managers, managers) on the data mining process.
Data Mining Resources, Books, Websites, White Papers, Presentations, Tutorials
Mr. Abbott is a seasoned instructor, having taught a wide range of data mining tutorials and seminars for a decade to audiences of up to 400, including DAMA, KDD, AAAI, and IEEE conferences. He is the instructor of well-regarded data mining courses, explaining concepts in language readily understood by a wide range of audiences, including analytics novices, data analysts, statisticians, and business professionals. Mr. Abbott also has taught applied data mining courses for major software vendors, including Clementine (SPSS), Affinium Model (Unica Corporation), Model 1 (Group1 Software), and hands-on courses using S-Plus and Insightful Miner (Insightful Corporation), and CART (Salford Systems).
By Abbott Analytics
- Data Mining and Predictive Analytics Blog
- Books with Contributions by Dean Abbott
- Papers
- Presentations and Tutorials
By External Sources
Books by Dean Abbott
- Applied Predictive Analytics: Principles and Techniques for the Professional Data Analyst, by Dean Abbott, April 2014, (use promo code APP14)
- IBM SPSS Modeler Cookbook, by Keith McCormick, Dean Abbott, Meta Brown, Tom Khabaza, Scott Mutchler, 2013
Books with Contributions by Dean Abbott
- Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners, by Jared Dean, Foreword
- Journeys to Data Mining: Experiences from 15 Renowned Researchers, Chapter Contributor (Springer, with Access to Full Chapter) (Amazon)
- Handbook of Statistical Analysis and Data Mining Applications, by Gary Miner, John Elder IV, and Robert Nisbet, Foreword #2
- Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications, by Gary Miner, John Elder IV, and Robert Nisbet, Foreword #3
Dean Abbott Referenced in Books
- Modern Analytics Methodologies, by Michele Chambers and Thomas Dinsmore, referenced on pages 26, 45-50, and 52
- The Power of Habit, by Charles Duhigg, referenced on page 224, Chapter 7
- Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, by Eric Siegel, referenced on pages 55, 143-144, and 148
- Investigative Data Mining for Security and Criminal Detection, by Jesus Mena, referenced on pages 213 and 219
Lists Featuring Dean Abbott
- 10 Most Influential People in Data Analytics, Monday, May 13, 2013
- 200 Big Data thought leaders to follow
- 180 leading data science, big data and analytics bloggers
- Top (11) influencers in Data Mining to follow
- Data Analytics: Experts to Follow on Twitter, By Techopedia Staff, July 3, 2014
- Most Influential in Data Mining
- Taxonomy of Data scientists, Posted by Vincent Granville on November 20, 2013
- 200+ Big Data thought leaders that everyone must follow on Twitter
Interviews with Dean Abbott
- Fortune: These big data companies are ones to watch, by Katherine Noyes @noyesk, June 13, 2014
- Popular Mechanics Online: Why The NSA Wants All That Verizon Metadata, June 6, 2013
- How do DATA SCIENTISTS determine RELIABILITY of DATA MINING – PREDICTIVE ANALYTIC models?
- Chief Marketer Magazine: Q & A with Data and Analytics Expert Dean Abbott, Fall 2014
- The Data Analytics Handbook, review of the book
- ComputerWorld: 8 Big Trends in Big Data Analytics, October 23, 2014
- Big Data Benefits Begin with Business Focus in Analytical Modeling, July 31, 2014
- DM Radio Broadcast Central: Blinded by Data Science
- Son of Gandhi: Decision Stats, September 30, 2010
- 4 Interview Questions for Data Miners, by Leslie Stevens-Huffman, September 24, 2014
- Avoiding the Creep Factor, July 2014
Webinars Featuring Dean Abbott
- The Briefing Room (TIbco): Analytic Maturity: Bringing Predictive into the Mainstream, June 2014
- The Briefing Room (Tableau): Analyzing Data in the Cloud, July 2013
- All Analytics, Beth Schultz: 5 Tips for Predictive Modeling Success, Beth Schultz, Editor in Chief, August 21, 2014
Papers and White Papers
- The Benefits of Creating Ensembles of Classifiers (HTML)
- The Benefits of Creating Ensembles of Classifiers (PDF)
National Committees
- KDD 2010 Conference, Industrial Track Committee
- Third Workshop on Data Mining Case Studies and Practice Prize (2009); Organizing Committee
- KDD 2006 Conference, Industrial Track Committee
- KDD 2004 Conference, Industrial Track Committee
Presentations and Tutorials
- DeVille, B., J. Caitlin, and D. Abbott, D., "Putting the Context Around Text Mining", Interview for DM Radio, April 17, 2008.
- "Hands-On Predictive Analytics", Instructor: Dean Abbott, to be presented at Predictive Analytics World Conference, San Francisco, CA, February 15, 2010.
- Abbott, D.W., "How to Improve Customer Acquisition Models with Ensembles", presented at Predictive Analytics World Conference, Washington, D.C., October 20, 2009.
- "Hands-On Predictive Analytics", Instructor: Dean Abbott, presented at Predictive Analytics World Conference, Washington, D.C., October 19, 2009.
- Fayyad, U., D. Abbott, and E. Martin"Text Analytics in the Contextual Enterprise", Interview for DM Radio, September 17, 2009.
- Abbott, D.W., "A Business-Centric Solution to Text Mining of Help Desk Data using CART", presented at Salford Systems Data Mining Conference, San Diego, CA, August 24, 2009.
- Abbott, D.W., "How to Improve Customer Acquisition Models with Ensembles", presented at Predictive Analytics World Conference, San Francisco, CA, February 16, 2009.
- DeVille, B., J. Caitlin, and D. Abbott, "Putting the Context Around Text Mining", Interview for DM Radio, April 17, 2008.
- Abbott, D. and B. Siegel, "Building More Accurate and Robust Customer Acquisition Models with Ensembles", Insightful Impact 2007, Atlantic City, NJ, October 10-11, 2007.
- Abbott, Dean, Survey Analysis: Data Mining vs. Standard Statistical Analysis of Survey Responses, A Paper Presented at Salford Systems Data Mining Conference 2006, San Diego, CA, March 29-31, 2006.
- Willard, T., D. Abbott, Data mining as a component of product stewardship: a case study with common ragweed., A Paper Presented at 59th Annual Meeting, Southern Weed Science Society, San Antonio, TX, January 23-25, 2006.
- Wroblewski, D., M.T. Green, J. Viloria, D. Abbott, and E. Wroblewska, Computational Platform for Predictive Toxicology, A Poster Presented at The ADMET 1 Conference, San Diego, CA, February 11-13, 2004.
- Abbott, Dean, Data Mining Essentials for Energy Companies, A pre-conference workshop at the 2nd Data Warehouse & Data Mining for Energy Companies, October 16-17, 2003.
- Abbott, Dean, Making Large Feature Sets Manageable for Prediction of LD50 from 3-D Chemical Structure (PDF), 7th Annual Insightful Users' Conference, Las Vegas, NV, October 8-10, 2003.
- Quoted in: Leon, Mark, Securing Business Intelligence Data, Computerworld, Data Management Special Report: Mining for Gems, April 14, 2003.
- Vafaie, H., D.W. Abbott, M. Hutchins, and I.P. Matkovsky, Improving Performance of Inductive Models Through an Algorithms and Sample Combination Strategy (PDF), International Journal on Artificial Intelligence Tools, Vol. 10, No. 4 (2001) 555-572.
- Abbott, D.W., Benefits of Creating Ensembles of Classifiers, The Data Administration Newsletter, Robert Seiner, ed., Issue 18, October 2001.
- Abbott, D.W., Model Ensembles in Clementine, SPSS 2000 Public Sector Users' Exchange, Washington, DC, December 6, 2000.
- Vafaie, H., D.W. Abbott, M. Hutchins, and I.P. Matkovsky, Combining Multiple Models Across Algorithms and Samples for Improved Results (PDF), The Twelfth International Conference on Tools with Artificial Intelligence, Vancouver, British Columbia, November 13-15, 2000.
- Abbott, D.W., H. Vafaie, M. Hutchins, and D. Riney, Improper Payment Detection in Department of Defense Financial Transactions (PDF - 320 KB), Federal Data Mining Symposium, Washington, DC, March 28-29, 2000.
- Abbott, D.W., Combining Models to Improve Classification Accuracy and Robustness (PDF), The 2nd International Conference On Information Fusion - FUSION'99, San Jose, CA, July 6, 1999.
- Abbott, D.W., New Advances in Data Mining, Greater Boston DAMA Day 1998, Cambridge, MA, Monday, November 30, 1998.
- Abbott, D.W., Modern Data Mining Methods, A Tutorial Presented at the 1998 IEEE International Conference on Systems, Man, and Cybernetics (SMC98), San Diego, CA, October 11, 1998.
- Abbott, D.W., I.P. Matkovsky, and J.F. Elder, An Evaluation of High-end Data Mining Tools for Fraud Detection, 1998 IEEE International Conference on Systems, Man, and Cybernetics, San Diego, CA, October 12-14, 1998.
- Elder, J.F., and D.W. Abbott, A Comparison of Leading Data Mining Tools (WinZip .zip file of a PDF, with screen captures - 3.8MB), (PDF file, no screen captures - 300KB), 4th International Conference on Knowledge Discovery and Data Mining (KDD-98), New York, NY, Friday, August 28, 1998.
- Abbott, D.W., Data Mining, Fraud Detection, and Prevention, A Workshop Presented at the Association of Government Accountants Technology and Fraud Seminar, Sacramento, CA, May 12, 1998.
- Abbott, D.W., Data Mining in Fraud Exploration, Association of Government Accountants, Monterey, CA, December 2, 1997.
Integrated Toxicity Assessment System (ITAS): Successful application of data mining by Abbott Analytics
TDWI Data Science Bootcamp Seminar (Austin, TX / Virtual Classroom): September 20 - 22, 2021
PAW for Business (Virtual Classroom): May 20 - 25, 2021
Vafaie, H., D.W. Abbott, M. Hutchins, and I.P. Matkovsky, Combining Multitple Models Across Algorithms and Samples for Improved Results (PDF), The Twelfth International Conference on Tools with Artificial Intelligence, Vancouver, British Columbia, November 13-15, 2000.