数据挖掘方法论-crisp介绍.ppt

CRISP-DM CSE634 Data Mining Prof. Anita Wasilewska Jae Hong Kil (105228510) References Pete Chapman (NCR), Julian Clinton (SPSS), Randy Kerber (NCR), Thomas Khabaza (SPSS), Thomas Reinartz, (DaimlerChrysler), Colin Shearer (SPSS) and Rüdiger Wirth (DaimlerChrysler) “CRISP-DM 1.0 - Step-by-step data mining guide” P. Gonzalez-Aranda, E.Menasalvas, S.Millan, F. Segovia “Towards a Methodology for Data Mining Project Development: The Importance of Abstraction” Laura Squier “What is Data Mining?” PPT “The CRISP-DM Model: The New Blueprint for DataMining”, Colin Shearer, JOURNAL of Data Warehousing, Volume 5, Number 4, p. 13-22, 2000 References Websites / /CRISPWP-800.pdf / / Overview Introduction to CRISP-DM Phases and Tasks Summary CRISP-DM CRoss-Industry Standard Process for Data Mining Why Should There be a Standard Process? The data mining process must be reliable and repeatable by people with little data mining background. Why Should There be a Standard Process? Framework for recording experience Allows projects to be replicated Aid to project planning and management “Comfort factor” for new adopters Demonstrates maturity of Data Mining Reduces dependency on “stars” Process Standardization Initiative launched in late 1996 by three “veterans” of data mining market. Daimler Chrysler (then Daimler-Benz), SPSS (then ISL) , NCR Developed and refined through series of workshops (from 1997-1999) Over 300 organization contributed to the process model Published CRISP-DM 1.0 (1999) Over 200 members of the CRISP-DM SIG worldwide - DM Vendors - SPSS, NCR, IBM, SAS, SGI, Data Distilleries, Syllogic, etc. - System Suppliers / consultants - Cap Gemini, ICL Retail, Deloitte Touche, etc. - End Users - BT, ABB, Lloyds Bank, AirTouch, Experian, etc. CRISP-DM Non-proprietary Application/Industry neutral Tool neutral Focus on business issues As well as technical analysis Framework for guidance Experience base Templates for Analysis CRISP-DM: Overview Da