evaluate.m ( File view )

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			function K = evaluate(ker, x1, x2)

% Evaluate a Gaussian radial basis kernel, for example
%    K = evaluate(kernel, x1, x2);
% where x1 and x2 are matrices containing input patterns, where each column
% represents a variable and each row represents an observation.

% File        : @rbf/evaluate.m
% Date        : Tuesday 12th September 2000 
% Author      : Dr Gavin C. Cawley
% Description : Evaluate a Gaussian radial basis kernel.  Part of an
%               object-oriented implementation of Vapnik's Support
%               Vector Machine, as described in [1].  
% References  : [1] V.N. Vapnik,
%                   "The Nature of Statistical Learning Theory",
%                   Springer-Verlag, New York, ISBN 0-387-94559-8,
%                   1995.
% Note        : A faster, memory efficient mex implementation is also suplied.
% History     : 07/07/2000 - v1.00
%               12/09/2000 - v1.01 minor improvements to comments and help
%                                  messages.
% Copyright   : (c) Dr Gavin C. Cawley, September 2000.
%    This program is free software; you can redistribute it and/or modify
%    it under the terms of the GNU General Public License as published by
%    the Free Software Foundation; either version 2 of the License, or
%    (at your option) any later version.
%    This program is distributed in the ho
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compilemex.m314.00 B11-03-03|16:49
correctness.m1.72 kB16-09-00|20:26
dagsvmdemo.m3.14 kB11-03-03|14:58
demo.m4.12 kB12-02-03|13:20
licence.txt17.92 kB16-09-00|20:26
readme.txt2.93 kB16-09-00|20:32
display.m1.56 kB16-09-00|20:26
evaluate.m1.85 kB16-09-00|20:26
char.m1.66 kB16-09-00|20:26
polynomial.m2.23 kB16-09-00|20:26
@polynomial0.00 B22-04-06|08:46
fwd.m1.99 kB28-11-00|11:16
train.m2.40 kB28-11-00|11:16
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train.m2.05 kB16-09-00|20:26
maxwin.m2.32 kB16-09-00|20:26
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display.m1.53 kB16-09-00|20:26
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linear.m1.93 kB16-09-00|20:26
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getnsv.m1.66 kB11-03-03|14:54
train.m2.12 kB28-11-00|11:16
dagsvm.m2.29 kB16-09-00|20:26
@dagsvm0.00 B22-04-06|08:46
manual.bbl1.14 kB16-09-00|20:26
manual.bib3.99 kB16-09-00|20:26
manual.aux1.21 kB16-09-00|20:26
manual.blg996.00 B16-09-00|20:26
manual.dvi7.30 kB16-09-00|20:26
manual.log5.05 kB16-09-00|20:26
manual.tex4.40 kB16-09-00|20:26
Makefile313.00 B16-09-00|20:26
manual.ps84.40 kB16-09-00|20:26
apalike.bst22.38 kB16-09-00|20:26
apalike.sty1.09 kB16-09-00|20:26
doc0.00 B22-04-06|08:46
iris.txt2.79 kB16-09-00|20:26
iris.names2.62 kB24-11-00|07:47
data0.00 B22-04-06|08:46
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fwd.m1.77 kB16-09-00|20:26
svc.m2.58 kB16-09-00|20:26
getkernel.m1.61 kB16-09-00|20:26
compact.m2.04 kB16-09-00|20:26
getbias.m1.59 kB16-09-00|20:26
.xialpha.m.swp12.00 kB16-09-00|20:29
strip.m2.00 kB16-09-00|20:26
getw.m1.55 kB16-09-00|20:26
getsv.m1.58 kB16-09-00|20:26
fixduplicates.m2.19 kB16-09-00|20:26
getnsv.m1.60 kB16-09-00|20:26
train.m1.71 kB16-09-00|20:26
xialpha.m2.87 kB16-09-00|20:26
@svc0.00 B22-04-06|08:46
InfCache.cpp2.34 kB16-09-00|20:26
smosvctutor.m2.06 kB16-09-00|20:26
Cache.h2.14 kB16-09-00|20:26
InfCache.h2.22 kB16-09-00|20:26
LrrCache.cpp4.28 kB17-11-00|13:34
compilemex.m1.76 kB31-01-03|09:19
SmoTutor.h2.75 kB16-09-00|20:26
smosvctrain.mexglx17.00 kB11-03-03|16:49
train.m3.02 kB16-09-00|20:26
SmoTutor.cpp10.02 kB17-11-00|13:33
LrrCache.h2.41 kB17-11-00|13:30
smosvctrain.cpp4.10 kB16-09-00|20:26
utils.hh1.45 kB16-09-00|20:26
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evaluate.c2.71 kB16-09-00|20:26
evaluate.m2.09 kB16-09-00|20:26
compilemex.m1.57 kB31-01-03|09:15
char.m1.67 kB16-09-00|20:26
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@rbf0.00 B22-04-06|08:46
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newsvm.zip74.74 kB26-10-01|14:23
nobias.m457.00 B06-08-98|16:39
qp.dll48.00 kB26-10-01|14:21
README2.58 kB12-10-01|15:27
softmargin.m312.00 B21-04-98|21:25
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svcoutput.m973.00 B21-04-98|21:24
svcplot.m3.04 kB12-10-01|01:50
svdatanorm.m1.27 kB23-06-98|11:09
svkernel.m2.55 kB11-10-01|15:44
svr.m3.89 kB21-08-98|15:36
svrerror.m1.17 kB21-08-98|10:33
svroutput.m711.00 B15-04-98|23:05
svrplot.m1.78 kB13-02-98|10:31
svtol.m401.00 B21-08-98|14:57
uiclass.m5.26 kB18-11-97|17:15
uiclass.mat12.30 kB18-11-97|17:15
uiregress.m5.50 kB27-09-97|22:42
uiregress.mat11.37 kB12-10-98|13:24
Makefile27.00 B11-10-01|15:14
pr_loqo.c16.34 kB11-10-01|15:14
pr_loqo.h2.33 kB11-10-01|15:14
qp.c7.08 kB11-10-01|15:14
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sinc.mat1.03 kB20-08-97|15:01
titanium.mat1.07 kB27-09-97|23:30
Regression0.00 B22-04-06|08:46
iris1v23.mat2.63 kB28-09-97|16:24
iris2v13.mat2.63 kB28-09-97|16:25
iris3v12.mat2.63 kB28-09-97|16:25
linsep.mat672.00 B06-11-97|15:46
nlinsep.mat712.00 B06-11-97|15:49
Classification0.00 B22-04-06|08:46
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svm(推荐)0.00 B22-04-06|08:46
SVM工具箱0.00 B22-04-06|08:46
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evaluate.m (287.68 kB)

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