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Data Mining Team 9. 정정정 정정정 정정정

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Data Mining. Team 9. 정세진 박미관 김세 호. DATA. 연관 관계 , 승패 예측 등의 정보. Best Player. 성향 분석. 승패 예측. 득점 분포. 승패 분포. 선수 기용 정보. Windows 7 64bits. IBM SPSS Modeler 14.2. MS Excel 97-2003. 선수별 성향 분석. 579 Record. 50 Record. Neural Network Algorithm. 결 과. Best Player. Data 가공 및 편집 - PowerPoint PPT Presentation

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Page 1: Data Mining

Data Mining

Team 9.정세진박미관김세호

Page 2: Data Mining
Page 3: Data Mining

DATA

연관 관계 , 승패 예측 등의 정보

Page 4: Data Mining

성향 분석 Best Player

득점 분포 승패 분포

승패 예측

선수 기용 정보

Page 5: Data Mining

Windows 7 64bitsIBM SPSS Mod-eler 14.2

MS Excel 97-2003

Page 6: Data Mining
Page 7: Data Mining
Page 8: Data Mining

선수별 성향 분석

579 Record

50 Record

Neural Network Algorithm

Page 9: Data Mining
Page 10: Data Mining

결과

Page 11: Data Mining

Best Player

Data 가공 및 편집

Graph Board

교차 표 기능

Page 12: Data Mining

결과

Page 13: Data Mining

승리 / 패배 시 득점분포

K-Means

Page 14: Data Mining

결과

Page 15: Data Mining

상대팀 별 승패 분포Graph 분포

Page 16: Data Mining

각 선수의 경기 기록을 이용한승패 예측

KNN Algo-rithm 70% Data 의 연관

관계에 따른 분석 필요

Page 17: Data Mining

결과

Page 18: Data Mining

중요한 순간의 선수 기용

3 점 슛 성공률4 쿼터 평균 점수

C5.0 Decision Tree Algorithm

Page 19: Data Mining

결과

Page 20: Data Mining

Thank you


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