代码搜索：patterns
找到约 8,017 项符合「patterns」的源代码
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www.eeworm.com/read/363091/9968058
doc nnutils.doc
NEURAL NET UTILITIES
version 1.01
by Gregory Stevens (stevens@prodigal.psych.rochester.edu)
www.eeworm.com/read/166872/9992142
asv getcenter.asv
function pattern=getCenter(p)
% 得到类心模式
if 0=get
pattern=mean(p.Patterns,2);
www.eeworm.com/read/359900/10116752
m bayesgauss.m
function d = bayesgauss(X, CA, MA, P)
%BAYESGAUSS Bayes classifier for Gaussian patterns.
% D = BAYESGAUSS(X, CA, MA, P) computes the Bayes decision
% functions of the n-dimensional patterns in
www.eeworm.com/read/418342/10952584
m bayesgauss.m
function d = bayesgauss(X, CA, MA, P)
%BAYESGAUSS Bayes classifier for Gaussian patterns.
% D = BAYESGAUSS(X, CA, MA, P) computes the Bayes decision
% functions of the n-dimensional patterns in
www.eeworm.com/read/466801/7020861
m bayesgauss.m
function d = bayesgauss(X, CA, MA, P)
%BAYESGAUSS Bayes classifier for Gaussian patterns.
% D = BAYESGAUSS(X, CA, MA, P) computes the Bayes decision
% functions of the n-dimensional patterns in
www.eeworm.com/read/456112/7357438
htm disc4.htm
Discussion fo Structural Patterns
function setFocus() {
if ((navigator.appName != "Netscape") && (parseFloat(navigator.appVersion) == 2)) {
return;
} else
www.eeworm.com/read/456112/7357917
htm preface-1.htm
Preface to CD
function setFocus() {
if ((navigator.appName != "Netscape") && (parseFloat(navigator.appVersion) == 2)) {
return;
} else {
self.foc
www.eeworm.com/read/456112/7358398
htm preface.htm
Preface to CD
function setFocus() {
if ((navigator.appName != "Netscape") && (parseFloat(navigator.appVersion) == 2)) {
return;
} else {
self.foc
www.eeworm.com/read/398324/7994459
m fwd.m
function y = fwd(net, x)
% FWD
%
% Compute the output of a dag-svm multi-class support vector classification
% network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, in
www.eeworm.com/read/398324/7994624
m fwd.m
function y = fwd(net, x)
% FWD
%
% Compute the output of a dag-svm multi-class support vector classification
% network.
%
% y = fwd(net, x);
%
% where x is a matrix of input patterns, in