新建 文本文档.txt

详细讲解了模式识别的算法理论

load d:\exercise\iris\train.txt
load d:\exercise\iris\test.txt
a=train(:,1:4);
b=test(:,1:4);
ma=mean(a(1:25,:));
ma(2:2,:)=mean(a(26:50,:));
ma(3:3,:)=mean(a(51:75,:));
mb=mean(b(1:25,:));
mb(2:2,:)=mean(b(26:50,:));
mb(3:3,:)=mean(b(51:75,:));
stda=std(a(1:25,:));
stda(2:2,:)=std(a(26:50,:));
stda(3:3,:)=std(a(51:75,:));
stdb=std(b(1:25,:));
stdb(2:2,:)=std(b(26:50,:));
stdb(3:3,:)=std(b(51:75,:));

?stda

stda =

    0.4005    0.3686    0.1979    0.1046
    0.5480    0.3527    0.4438    0.2063
    0.7242    0.3612    0.6461    0.2551

?stdb

stdb =

    0.3037    0.3906    0.1492    0.1118
    0.4813    0.2767    0.4983    0.1913
    0.5485    0.2784    0.4339    0.2971

?ma =

    5.0280    3.4800    1.4600    0.2480
    6.0120    2.7760    4.3120    1.3440
    6.5760    2.9280    5.6400    2.0440

?mb

mb =

    4.9840    3.3560    1.4680    0.2400
    5.8600    2.7640    4.2080    1.3080
    6.6000    3.0200    5.4640    2.0080

?sigma1=cov(a(1:25,:))

sigma1 =

    0.1604    0.1181    0.0241    0.0194
    0.1181    0.1358    0.0062    0.0223
    0.0241    0.0062    0.0392    0.0066
    0.0194    0.0223    0.0066    0.0109

?sigma2=cov(a(26:50,:))

sigma2 =

    0.3003    0.1095    0.1865    0.0520
    0.1095    0.1244    0.0886    0.0465
    0.1865    0.0886    0.1969    0.0640
    0.0520    0.0465    0.0640    0.0426

?sigma3=cov(a(51:75,:))

sigma3 =

    0.5244    0.1215    0.4322    0.0619
    0.1215    0.1304    0.0988    0.0604
    0.4322    0.0988    0.4175    0.0673
    0.0619    0.0604    0.0673    0.0651

sigma_1=inv(cov(a(1:25,:)))

sigma_1 =

   20.9151  -19.0249  -11.2193    8.2970
  -19.0249   28.5286   12.4840  -31.7589
  -11.2193   12.4840   34.8879  -26.4714
    8.2970  -31.7589  -26.4714  157.2867

?sigma_2=inv(cov(a(26:50,:)))

sigma_2 =

    9.5256   -4.4293   -9.4390    7.4140
   -4.4293   16.3236    1.7437  -15.0557
   -9.4390    1.7437   19.7833  -20.1460
    7.4140  -15.0557  -20.1460   61.2028

?sigma_3=inv(cov(a(51:75,:)))

sigma_3 =

   15.0399   -5.4507  -15.3497    6.6272
   -5.4507   16.1401    4.0828  -14.0152
  -15.3497    4.0828   18.6957   -8.5254
    6.6272  -14.0152   -8.5254   30.8896

a1=diag((a-ones(75,1)*mean(a(1:25,:)))*inv(cov(a(1:25)))*(a-ones(75,1)*mean(a(1:25,:)))')

a1 =

    0.0716
    1.5750
    1.3332
    2.0662
    0.1314
    2.4651
    1.2210
    0.0691
    4.5919
    1.1487
    1.1886
    0.5004
    1.9191
    5.6839
    5.8360
    8.2445
    2.2657
    0.0741
    3.8289
    0.6974
    1.2758
    0.4880
    2.5649
    0.9891
    1.5850
   98.4327
   79.5962
  106.2740
   57.1794
   87.6145
   70.1992
   87.1134
   32.0001
   85.8543
   49.3581
   43.1225
   62.7419
   59.8397
   82.9646
   39.5796
   80.4738
   70.8499
   54.4743
   86.1485
   49.6598
   89.7762
   57.1570
   99.6020
   81.1271
   71.0020
  170.3729
  107.1042
  172.4522
  134.0288
  156.0965
  228.7248
   76.8337
  195.3004
  155.8298
  195.3029
  115.7134
  124.4473
  144.1215
  106.0446
  118.0496
  130.3787
  131.6901
  240.0367
  260.0350
  103.9827
  160.6342
   97.8144
  237.6631
  102.6513
  151.0627

?exp(-a1/2)

ans =

    0.9648
    0.4550
    0.5135
    0.3559
    0.9364
    0.2915
    0.5431
    0.9660
    0.1007
    0.5631
    0.5520
    0.7786
    0.3831
    0.0583
    0.0540
    0.0162
    0.3221
    0.9636
    0.1474
    0.7056
    0.5284
    0.7835
    0.2774
    0.6098
    0.4527
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000

a2=diag((a-ones(75,1)*mean(a(26:50,:)))*inv(cov(a(26:50)))*(a-ones(75,1)*mean(a(26:50,:)))')

a2 =

   37.1150
   36.8845
   40.9036
   37.6825
   38.2713
   31.1443
   39.8073
   35.4005
   41.3046
   35.9560
   34.7837
   35.0422
   38.4538
   49.4414
   41.7509
   38.4099
   38.6363
   36.3863
   30.1679
   36.2265
   29.6243
   34.9156
   49.7917
   28.7784
   29.9227
    4.3615
    1.2988
    4.2083
    1.9583
    1.1523
    0.4503
    1.9103
    8.3939
    1.4853
    2.7909
    8.0062
    0.3317
    1.8237
    0.5888
    2.3113
    1.9623
    0.9312
    0.7127
    1.4214
    1.5826
    2.1261
    0.3583
    1.7624
    0.5981
    0.5595
   15.1306
    3.2664
   14.4112
    6.5448
   10.7744
   27.9032
    4.9116
   19.4307
    9.8965
   22.0591
    4.8930
    4.8011
    8.8388
    3.5875
    5.9334
    7.3948
    6.3530
   34.4134
   34.9423
    2.7629
   12.6847
    3.1519
   29.9161
    2.1394
   10.8104

?exp(-a2/2)

ans =

    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.0000
    0.1130
    0.5223
    0.1220
    0.3756
    0.5621
    0.7984
    0.3848
    0.0150
    0.4758
    0.2477
    0.0183
    0.8472
    0.4018
    0.7450
    0.3149
    0.3749
    0.6278
    0.7002
    0.4913
    0.4533
    0.3454
    0.8360
    0.4143
    0.7415
    0.7560
    0.0005
    0.1953
    0.0007
    0.0379
    0.0046
    0.0000
    0.0858
    0.0001
    0.0071
    0.0000
    0.0866
    0.0907
    0.0120
    0.1663
    0.0515
    0.0248
    0.0417
    0.0000
    0.0000
    0.2512
    0.0018
    0.2068
    0.0000
    0.3431
    0.0045

?a3=diag((a-ones(75,1)*mean(a(51:75,:)))*inv(cov(a(51:75)))*(a-ones(75,1)*mean(a(51:75,:)))')

a3 =

   45.5448
   46.1329
   49.2550
   46.6707
   46.3640
   39.1955
   47.9529
   44.3297
   49.7973
   45.3038
   42.9422
   44.0482
   47.5135
   56.3999
   47.4167
   43.4334
   45.5112
   44.8606
   38.3160
   44.0887
   39.1489
   43.1291
   55.8469
   38.5669
   39.5974
    2.9598
    3.2427
    1.8652
    9.1443
    2.6691
    5.0284
    2.4701
   18.4083
    3.1207
   10.2740
   17.1901
    5.3999
    8.8507
    2.9094
   10.8095
    3.8087
    4.8690
    7.8484
    4.3228
    9.6386
    2.4716
    6.6478
    2.1032
    3.5067
    4.5402
    1.0528
    1.8431
    0.6684
    0.2633
    0.1161
    3.7729
    8.4098
    1.9453
    0.5410
    2.4037
    0.7119
    0.4182
    0.1489
    2.5974
    1.9773
    0.5456
    0.1718
    6.0482
    5.7668
    2.9887