The arboretum procedure



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   61 BIAS_H1      1.621410 3.94302E-7 BIAS -> H1

   62 BIAS_H2      1.544387 -0.0000555 BIAS -> H2

   63 BIAS_H3     -0.534732  0.0000123 BIAS -> H3

   64 BIAS_H4     -0.785714 -0.0000101 BIAS -> H4

   65 BIAS_H5      0.912585 -0.0000115 BIAS -> H5

   66 BIAS_H6     -0.768781 -2.2982E-6 BIAS -> H6

   67 BIAS_H7      1.015622 -9.1444E-6 BIAS -> H7

   68 BIAS_H8      0.550634 -1.1615E-8 BIAS -> H8

   69 BIAS_H9     -2.030613 -0.0000519 BIAS -> H9

   70 BIAS_H10     0.306667 -9.3574E-6 BIAS -> H10

   71 BIAS_H11    -2.591558  0.0000337 BIAS -> H11

   72 BIAS_H12     1.854141  0.0000213 BIAS -> H12

   73 BIAS_H13    -0.378726 -0.0000290 BIAS -> H13

   74 BIAS_H14    -0.596093 -0.0000340 BIAS -> H14

   75 BIAS_H15     1.200441 -0.0000417 BIAS -> H15

   76 BIAS_H16    -1.358588  0.0000232 BIAS -> H16

   77 BIAS_H17    -2.473932  0.0000370 BIAS -> H17

   78 BIAS_H18    -1.391321  0.0000284 BIAS -> H18

   79 BIAS_H19    -1.537930 -0.0000246 BIAS -> H19

   80 BIAS_H20     0.717883 -0.0000180 BIAS -> H20

   81 BIAS_H21     0.046762 -0.0000347 BIAS -> H21

   82 BIAS_H22    -0.062103 -0.0000241 BIAS -> H22

   83 BIAS_H23     0.090229  0.0000343 BIAS -> H23

   84 BIAS_H24     0.502362 1.47214E-6 BIAS -> H24

   85 BIAS_H25    -2.014471 -3.7539E-6 BIAS -> H25

   86 BIAS_H26    -0.448834 7.76322E-6 BIAS -> H26

   87 BIAS_H27     2.068868  0.0000197 BIAS -> H27

   88 BIAS_H28     1.888770  0.0000405 BIAS -> H28

   89 BIAS_H29     0.249710 -6.3913E-6 BIAS -> H29

   90 BIAS_H30     3.409735 8.33278E-6 BIAS -> H30

   91 H1_HIPL     -0.110538  0.0000178 H1 -> HIPL

   92 H2_HIPL     -0.473553 -0.0000117 H2 -> HIPL

   93 H3_HIPL     -1.150299  0.0000209 H3 -> HIPL

   94 H4_HIPL      0.477358 -4.1644E-6 H4 -> HIPL

   95 H5_HIPL      0.464599  0.0000156 H5 -> HIPL

   96 H6_HIPL      0.868824  0.0000395 H6 -> HIPL

   97 H7_HIPL     -0.305023 2.29377E-6 H7 -> HIPL

   98 H8_HIPL     -0.022398  0.0000134 H8 -> HIPL

   99 H9_HIPL     -0.971155 -0.0000579 H9 -> HIPL

  100 H10_HIPL     0.974106 -0.0000192 H10 -> HIPL

                    Optimization Results

                    Parameter Estimates

 ------------------------------------------------------

   Parameter       Estimate   Gradient Label

 ---------------------------------------------------

  101 H11_HIPL     0.568802 -0.0000519 H11 -> HIPL

  102 H12_HIPL     1.227553  0.0000166 H12 -> HIPL

  103 H13_HIPL    -0.466255 -0.0000231 H13 -> HIPL

  104 H14_HIPL    -0.894798 -0.0000322 H14 -> HIPL

  105 H15_HIPL    -1.479547 -2.2118E-6 H15 -> HIPL

  106 H16_HIPL     0.471993  0.0000190 H16 -> HIPL

  107 H17_HIPL    -0.695108 -0.0000138 H17 -> HIPL

  108 H18_HIPL     0.411108 -9.7179E-7 H18 -> HIPL

  109 H19_HIPL    -0.650073 2.01526E-7 H19 -> HIPL

  110 H20_HIPL    -1.728201  0.0000190 H20 -> HIPL

  111 H21_HIPL    -0.845374  0.0000182 H21 -> HIPL

  112 H22_HIPL     0.907477 -0.0000158 H22 -> HIPL

  113 H23_HIPL     0.890942  0.0000194 H23 -> HIPL

  114 H24_HIPL     0.670337 -0.0000501 H24 -> HIPL

  115 H25_HIPL     0.524875 -0.0000589 H25 -> HIPL

  116 H26_HIPL     0.644267 -0.0000242 H26 -> HIPL



  117 H27_HIPL    -0.968536 -4.3518E-6 H27 -> HIPL

  118 H28_HIPL    -0.283694  1.1348E-6 H28 -> HIPL

  119 H29_HIPL     0.366848 -2.7894E-6 H29 -> HIPL

  120 H30_HIPL     0.731690  0.0000279 H30 -> HIPL

  121 BIAS_HIP    -0.008245  0.0000135 BIAS -> HIPL

                   Value of Objective Function = 0.0007488987



PROC PRINT Report of the Average Squared Error for the Scored Test Data Set

                          Hill & Plateau Data

                             MLP with 30 Hidden Units

                         Fit Statistics for the Test Data

                                     Test:

                                    Average

                                    Squared

                                     Error.

                                   .00071717

GCONTOUR Plot of the Predicted Values



G3D Plot of the Predicted Values

Copyright 2000 by SAS Institute Inc., Cary, NC, USA. All rights reserved.




 

The %LET statement sets the macro variable HIDDEN to 3.

title 'Hill & Plateau Data';

%let hidden=3;




 

The MAXITER = option specifies the maximum number of iterations.

   hidden &hidden / id=h;

   prelim 10;

   train maxiter=1000 outest=mlpest;

   score data=sampsio.dmtsurf out=mlpout outfit=mlpfit;

   title2 "MLP with &hidden Hidden Units";

run;



 

PROC PRINT creates a report of selected fit statistics.

proc print data=mlpfit noobs label;

   var _tase_  _tasel_ _taseu_;

   where _name_ ='HIPL';

   title3 'Fit Statistics for the Test Data';

 run;



 

PROC GCONTOUR creates a plot of the predicted values.

proc gcontour data=mlpout;

   plot x2*x1=p_hipl / pattern ctext=black coutline=gray;

   pattern v=msolid;

   legend frame;

   title3 'Predicted Values';

   footnote;

run;





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