1 jiawei Han 2 1Intelligent miner for data 2SAS

data mining 1990 19901002110

1863963 2 32000 4 5

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1 * * * * yyy

2 * * 99%VaR *

1 STSTt-2t y y=0 y=1

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3CSMAR 1990-2004 1990-1997 1998-2004 4 1994 1998

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sj0 * 1995 * * 1996-20011998-2003 * * ST1008ST111 * 6 ///+//

SAS * EXCELSAS * SASuniformseedseed[01] * SAS # data a set sasuser.sj0; k=uniform(15); run; # ka data b; set a; m=int(_n_/2); run; sj1sj2

1

SAS proc discrim data=sasuser.sj1; class y; run; SAS

* * d = 1.2 dd1.2d1.2 ST49/56=87.5% 47/55 = 85.4% ST: 442/504=87.7% 432/504 = 85.7%

* * * * * sj1sj2

2Logistic Logistic

Logistic LogisticSAS proc logistic descending data=sasuser.Sj1 model y = x1-x6; run; SAS :0.09,: P0.09,;P0.09,.

ST 46/56=82.1% 44/55=80% ST 433/504=85.9% 425/504=84.3% * * * *

Logistic 15y1-y151119 SAS proc logistic descending data=sasuser.sj00; model y=y1-y15 / selection=stepwise; run;

SAS Logistic y3y4y5y6y10y11y12y13y14 P0.09,;P0.09, ST 92/111 = 82.9%; ST 864/1008 = 85.71%.

3Probir Probit

Probit ProbitSAS proc probit data=sasuser.sj1; class y;(Logistic) model y=x1-x6; run;

:

: P>0.1 St 46/56=82.1 46/55=83.6 St 428/504=84.9 419/504=83.1

4 y

x y x

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