代码搜索:parameter

找到约 10,000 项符合「parameter」的源代码

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m cp0201_bits.m

% % FUNCTION 2.1 : "cp0201_bits" % % Generates a stream of equiprobable binary values ('bits') % The number of bits ('numbits') is an input parameter % % Programmed by Guerino Giancola % fun
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m cp0201_bits.m

% % FUNCTION 2.1 : "cp0201_bits" % % Generates a stream of equiprobable binary values ('bits') % The number of bits ('numbits') is an input parameter % % Programmed by Guerino Giancola % fun
www.eeworm.com/read/441245/7672641

m ridger.m

%RIDGER Ridge Regression % % W = RIDGER(X,LAMBDA) % % INPUT % X Regression dataset % LAMBDA Regularization parameter (default LAMBDA=1) % % OUTPUT % W Ridge regression mappin
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m ksmoothr.m

%KSMOOTHR Kernel smoother % % W = KSMOOTHR(X,H) % % INPUT % X Regression dataset % H Width parameter (default H=1) % % OUTPUT % W Kernel smoother mapping % % DESCRIPTION % Train a
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m parzenml3.m

%PARZENML Optimum smoothing parameter in Parzen density estimation. % % H = PARZENML(A,FID) % % INPUT % A input dataset % FID File ID to write progress to (default [], see PRPROGRESS) % %
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m parzenml.m

%PARZENML Optimum smoothing parameter in Parzen density estimation. % % H = PARZENML(A) % % INPUT % A Input dataset % % OUTPUT % H Scalar smoothing parameter (in case of crisp labels) %
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m get.m

%GET Get datafile parameter fields % % [VALUE1,VALUE2,...] = GET(A,FIELD1,FIELD2,...) % % INPUT % A Datafile % FIELDx Field names (strings) % % OUTPUT % VALUEx Field values % % SEE A
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m lassor.m

%LASSOR LASSO regression % % W = LASSOR(X,LAMBDA) % % INPUT % X Regression dataset % LAMBDA Regularization parameter % % OUTPUT % W LASSO regression mapping % % DESCRIPTION % Th
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m sigm.m

%SIGM Sigmoid map % % W = W*SIGM % B = A*SIGM % W = W*SIGM([],SCALE) % B = SIGM(A,SCALE) % % INPUT % A Dataset (optional) % SCALE Scaling parameter (optional, default: 1) % %
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resharper wawatextcluster.resharper