代码搜索：Variables
找到约 10,000 项符合「Variables」的源代码
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www.eeworm.com/read/182374/9205857
m runfda.m
function [Max,k,BestSolutions]=RunFDA(PopSize,NumbVar,T,F,CantGen,MaximumFunction,Card,Cliques,Elitism)
% The only difference between this FDA implementation for the HP protein model
% and the ma
www.eeworm.com/read/181830/9235675
m iszero.m
function yesno = iszero(S)
% ISZERO -- checks whether a symbolic matrix contains only zeros
%
% yesno = iszero(S)
%
% If the symbolic matrix S contains only entries which can be
% converted to
www.eeworm.com/read/378044/9252882
inc ram.inc
* Ram.inc
**********************************************************************
* Ram variables *
*******************************************
www.eeworm.com/read/375719/9351848
m sdmsol.m
function [quiz,sdmdata] = sdmsol(quiz,pars,Rayon)
% SDMPB/SDMSOL - solve a linear matrix problem with SeDuMi
%
% quiz = sdmsol(quiz,pars,Radius);
%
% solve an optimization problem defined by the S
www.eeworm.com/read/375212/9368866
m plscv1.m
function [press,cumpress,minlv,b,r,w,p,qlim,t2lim,tvar] = plscv1(x,y,lv,np,mc)
%PLSCV1 Leave-one-out cross validation for PLS models
% Inputs are the matrix of predictor variables (x), matrix
% o
www.eeworm.com/read/375212/9369091
m polypred.m
function ypred = polypred(x,b,p,q,w,lv)
%POLYPRED Prediction with POLYPLS models
% The inputs are the matrix of predictor variables (x),
% the POLYPLS model inner-relation coefficients (b), the
www.eeworm.com/read/375212/9369262
m replace.m
function rm = replace(r,vars)
%REPLACE Replaces variables based on PCA or PLS models
% This function generates a matrix that can be used to
% replace "bad" variables from data matrices with the
www.eeworm.com/read/375212/9369269
m rsgndemo.m
echo on
%RSGNDEMO Demonstrates PLSRSGN and PCA for use in MSPC
% This is a demonstration of the PLSRSGN and PCA functions
% that shows how they can be used for multivariate statistical
% process c
www.eeworm.com/read/375075/9373452
m bnloocv.m
function Ehat = bnLOOCV(X,Y,w,k,F,bi)
% Ehat = bnLOOCV(X,Y,w,k,F,bi) - LOOCV for Boolean Network inference
%
% Function estimates the (possibly weighted) error of all predictor
% variable (rows
www.eeworm.com/read/375075/9373454
m bnsteadystateerrors.m
function [Ehat,Fhat] = bnSteadyStateErrors(eem,X,w,k,F,bi,nr,cvk)
% [Ehat,Fhat] = bnSteadyStateErrors(eem,X,w,k,F,bi,nr,cvk) - Predictor inference
%
% Function estimates the (possibly weighted) p