1. Megaputer Intelligence 2000. 3. 27 인공지능연구실 석사 2 학기 최윤정 (cris@ai.ewha.ac.kr)

2. Outline  Overview Overview  Technology Technology  PolyAnalyst solution overview PolyAnalyst solution overview  Customer cases Customer cases  Future developments Future developments

3. Megaputers… Overview 1989 년 모스크바 주립대학 AI 연구소  Knowledge Discovery  Semantic 정보검색 및 분석에 기반을 둠. 1994 년 Polyanalyst1.0 개발 2000

4. Technology O Subject-Oriented analytical systems O Statistical packages O Neural Networks O Evolutionary Programming O Memory Based Reasoning(MBR) O Decision Tress O Genetic Algorithms

5. 데이타마이닝과 지식탐사를 위한 툴과 semantic Text 분석, information retrieval 을 위한 툴 제공 O PolyAnalyst 4.0 O PolyAnalyst COM O TextAnalyst 1.5 O TextAnalyst Com O MegaSearch tm Product

6. PolyAnalyst overview

7. Features in more detail  multi-strategy data mining suite O utilizing the latest achievements in knowledge discovery O with a broad selection of exploration engines O powerful data manipulation and visualization tools O Modeling O Predicting O Clustering O Classifying O Explaining

8. PolyAnalyst workplace Multiple machine learning algorithms can be accessed through pull-down and pop-up menus, or control buttons The project data, charts, discovered rules, and system reports are represented by icons held in separate containers

9. Learning algorithms Find Dependencies PolyNet Predictor Cluster Find Laws Classify Discriminate Linear Regression Identifies a set of the most influential predictors and determines outliers Predicts values of the target variable - a hybrid of GMDH and Neural Net algorithms Separates groups of similar records and finds the best clustering variables Finds an explicit model for the relation predicting the target variable Assigns cases to two different classes by utilizing Fuzzy Logic Determines what characteristics of a specified data set distinguish it from the rest of the data Stepwise linear regression - correctly treats categorical and yes/no variables New algorithm: robustly classifies records into multiple categories Memory Based Reasoning PolyAnalyst COM

10. Find Dependencies Outliers Most influential variables determined Predicted target value for a cell All considered variables

11. Cluster Variables providing the best clustering Individual clusters Cluster sequential number Number of points in a cluster

12. PolyNet Predictor R^2 = 0.93 Linear Regression R^2 = 0.86 Similar to all other PolyAnalyst algorithms the best PN model is found as an optimal solution in terms of The following graphs display the accuracy of PN and LR models developed to predict relative performance of computers from different manufacturers: Predicted vs. Actual target variable

13. Classify Mass mailing Targeted mailing PolyAnalyst Lift chart illustrates an increase in the response to a campaign based on the discovered model - instead of random mailing % of maximal possible response Mass mailing Targeted mailing Profit ($) PolyAnalyst Gain chart helps optimize the profit obtained in a direct marketing campaign

14. Linear Regression Yes/no variable taken into account correctly Partial contributions of individual terms in the linear regression formula

15. Discriminate algorithm  Determines what features of a selected data set distinguish it from the rest of the data  Requires no preset target variable  Can be powered by Find Laws PolyNet Predictor Linear Regression Memory-Based Reasoning  Performs classification to multiple categories  Is based on identifying similar cases in the previous history  Implemented only in PolyAnalyst COM (available in the end of March 1999)

16. Data Access  PolyAnalyst works with ODBC-compliant databases: Oracle, DB2, Informix, Sybase, MS SQL Server, etc.  A customized version works with IBM Visual Warehouse Solution and Oracle Express  Data and exploration results can be exchanged with MS Excel  CSV or DBF format files  New data can be added to the project when necessary

17. Visualization Data can be displayed in various visual formats:  Histograms  Line and point plots with zoom and drill-through capabilities  Colored charts for three dimensions  Interactive rule-graphs with sliders help visualizing and manipulating multi-variable relations  Frequencies charts provide for a quick and thorough visualization of the distribution of categorical, integer, or yes/no variables  Lift and Gain charts are very useful in marketing applications

18. Histograms and Frequencies Histogram displays distribution of numerical variables Frequencies chart displays distribution of categorical and yes/no variables

19. 2D charts and Rule-graphs Sliders help visualize effects of other variables in more than two-dimensional models The Find Laws model (red line) for a product market share dependence on the price predicts a dramatic change in the formula when the product goes on promotion

20. PolyAnalyst platforms  Standalone system: PolyAnalyst Power - Windows 95/98/NT PolyAnalyst Pro - Windows NT PolyAnalyst Lite - Windows 95/98/NT PolyAnalyst 2.1 - IBM OS/2  Client/Server system: PolyAnalyst Knowledge Server - Windows NT or OS/2 Client - Windows NT, 95, 98, or OS/2

21. Sample customer cases

22. PolyAnalyst supports medical projects at 3M Timothy Nagle Consulting Scientist 3M Corporation St. Paul, MN, USA “ Analytical engines do an excellent job of finding relations amongst many fields without overfitting. I found the user interface both intuitive and easy to use. Megaputer support is outstanding. The inevitable problems one expects with a complex system are dealt with immediately. ”

23. PolyAnalyst helps improving flight control system at Boeing James Farkas Senior Navigation Engineer The Boeing Company Kent, WA, USA “ PolyAnalyst provides quick and easy access for inexperienced users to powerful modeling tools. The user interface is intuitive and new users come up to speed very quickly. Interfaces to spreadsheet tools provide flexibility needed to work solutions as a team. ”

24. PolyAnalyst facilitates marketing research at Indiana University Raymond Burke E.W. Kelley Professor of BA Kelley Business School Indiana University Bloomington, IN, USA “ PolyAnalyst provides a unique and powerful set of tools for data mining applications, including promotion response analysis, customer segmentation and profiling, and cross-selling analysis. Unlike neural network programs, PolyAnalyst displays a symbolic representation of the relationship between the independent and dependent variables - a critical advantage for business applications. ”

25. PolyAnalyst helps medical research at the University of Wisconsin-Madison Prof. Roger L. Brown Director of RDSU University of Wisconsin Madison, WI, USA “ PolyAnalyst suite enabled our researchers to search their data for rules and structure while providing a symbolic knowledge of the structure, the detail they needed. The software has provided very interesting results for one of our projects, which had been presented at a major cardiology meeting. ”

26. PolyAnalyst enjoys international success “ PolyAnalyst scores extremely well by providing a complete environment in which almost any research worker could data mine his or her own data. It is a very useful product, potentially with a wide user base, and it appears to me to be unique. ” “ PolyAnalyst proves capable of providing models for building reliable trading strategies even for a difficult to predict FOREX market. PolyAnalyst is a leader in reliability, accuracy, and diversity of automatically built models. ” Alexander Fomenko Director Analytical Dept Killiney Investments Europe Rep. Moscow, Russia David McIlroy Analytical Department Master Foods Olen, Belgium

27. Product Price $$ Custom-build own PolyAnalyst system!

28. Product Price $$(continue) Custom-build own PolyAnalyst system! - COM 모듈은 어플리케이션을 작성하는데 적당 - 각각의 필요한 알고리즘에 해당하는 Tool Kit 을 구입할 수 있음

29. Future developments  New machine learning algorithms: Memory Based Reasoning Weighted variable Clustering and Classification  PolyAnalyst COM built on the basis of Component Object Model - an integrated kit for simple development of decision support applications utilizing advanced PolyAnalyst algorithms (see PCAI Magazine, March 99, p. 16-19)  Enhanced graphics (Snake and Boxplot charts) and data import and manipulation

30. PolyAnalyst evaluation www.megaputer.com