代码搜索：factor
找到约 6,651 项符合「factor」的源代码
代码结果 6,651
www.eeworm.com/read/199525/5076197
entries
8
dir
1124
https://mosesdecoder.svn.sourceforge.net/svnroot/mosesdecoder/trunk/regression-testing/tests/multi-factor-drop/truth
https://mosesdecoder.svn.sourceforge.net/svnroot/mosesdecoder
2006-0
www.eeworm.com/read/197905/5090892
m mfa.m
% function [Lh,Ph,Mu,Pi,LL]=mfa(X,M,K,cyc,tol);
%
% Maximum Likelihood Mixture of Factor Analysis using EM
%
% X - data matrix
% M - number of mixtures (default 1)
% K - number of factors in each mix
www.eeworm.com/read/167728/5454197
changelog
2003-08-11 Brian Gough
* test_sf.c: added preprocessor definitions TEST_FACTOR and
TEST_SIGMA to allow larger tolerances on released versions (to
reduce the number of
www.eeworm.com/read/346158/3189478
m mfa.m
% function [Lh,Ph,Mu,Pi,LL]=mfa(X,M,K,cyc,tol);
%
% Maximum Likelihood Mixture of Factor Analysis using EM
%
% X - data matrix
% M - number of mixtures (default 1)
% K - number of factors in each mix
www.eeworm.com/read/344585/3208008
m mppca.m
function [LX, MX, PX] = mppca(X, no_dims, no_analyzers, tol, maxiter, minstd)
%MPPCA Runs EM algorithm and computes local factor analyzers
%
% [LX, MX, PX] = mppca(X, no_dims, no_analyzers, tol, max
www.eeworm.com/read/307266/3725982
c pollard.c
/*
* Program to factor big numbers using Pollards (p-1) method.
* Works when for some prime divisor p of n, p-1 has itself
* only small factors.
* See "Speeding the Pollard and Elliptic Cu
www.eeworm.com/read/307266/3726327
c pollard.c
/*
* Program to factor big numbers using Pollards (p-1) method.
* Works when for some prime divisor p of n, p-1 has itself
* only small factors.
* See "Speeding the Pollard and Elliptic Cu
www.eeworm.com/read/303435/3811375
lib pfafft.cwp.lib
PFAFFT - Functions to perform Prime Factor (PFA) FFT's, in place
npfa return valid n for complex-to-complex PFA
npfar return valid n for real-to-complex/complex-to-real PFA
npfao return optimal n
www.eeworm.com/read/292984/3935718
m mfa.m
% function [Lh,Ph,Mu,Pi,LL]=mfa(X,M,K,cyc,tol);
%
% Maximum Likelihood Mixture of Factor Analysis using EM
%
% X - data matrix
% M - number of mixtures (default 1)
% K - number of factors in each mix
www.eeworm.com/read/292964/3936866
m mfa.m
% function [Lh,Ph,Mu,Pi,LL]=mfa(X,M,K,cyc,tol);
%
% Maximum Likelihood Mixture of Factor Analysis using EM
%
% X - data matrix
% M - number of mixtures (default 1)
% K - number of factors in each mix