首页| JavaScript| HTML/CSS| Matlab| PHP| Python| Java| C/C++/VC++| C#| ASP| 其他|
购买积分 购买会员 激活码充值

您现在的位置是:虫虫源码 > Matlab > em 算法,可以直接调用

em 算法,可以直接调用

资 源 简 介

该算法,是基本的Em算法,可以直接调用,经过试验真的很不错,另外里面还有很多源代码,每个源代码都可以直接调用,算法中含有比较细致的描述。

文 件 列 表

AR_to_SS.m
convert_to_lagged_form.m
ensure_AR.m
eval_AR_perf.m
kalman_filter.m
kalman_forward_backward.m
kalman_smoother.m
kalman_update.m
learning_demo.m
learn_AR.m
learn_AR_diagonal.m
learn_kalman.m
README.txt
README.txt~
sample_lds.m
smooth_update.m
SS_to_AR.m
testKalman.m
tracking_demo.m
beta_sample.m
chisquared_histo.m
chisquared_prob.m
chisquared_readme.txt
chisquared_table.m
clg_Mstep.m
clg_Mstep_simple.m
clg_prob.m
condGaussToJoint.m
condgaussTrainObserved.m
condgauss_sample.m
cond_indep_fisher_z.m
convertBinaryLabels.m
cwr_demo.m
cwr_em.m
cwr_predict.m
cwr_prob.m
cwr_readme.txt
cwr_test.m
dirichletpdf.m
dirichletrnd.m
dirichlet_sample.m
distchck.m
eigdec.m
est_transmat.m
fit_paritioned_model_testfn.m
fit_partitioned_model.m
gamma_sample.m
gaussian_prob.m
gaussian_sample.m
histCmpChi2.m
KLgauss.m
linear_regression.m
logist2.m
logist2Apply.m
logist2ApplyRegularized.m
logist2Fit.m
logist2FitRegularized.m
logistK.m
logistK_eval.m
marginalize_gaussian.m
matrix_normal_pdf.m
matrix_T_pdf.m
mc_stat_distrib.m
mixgauss_classifier_apply.m
mixgauss_classifier_train.m
mixgauss_em.m
mixgauss_init.m
mixgauss_Mstep.m
mixgauss_prob.m
mixgauss_prob_test.m
mixgauss_sample.m
mkPolyFvec.m
mk_unit_norm.m
multinomial_prob.m
multinomial_sample.m
multipdf.m
multirnd.m
normal_coef.m
partial_corr_coef.m
parzen.m
parzenC.c
parzenC_test.m
parzen_fit_select_unif.m
pca.m
README.txt
rndcheck.m
sample.m
sample_discrete.m
sample_gaussian.m
standardize.m
student_t_logprob.m
student_t_prob.m
test_dir.m
unidrndKPM.m
unif_discrete_sample.m
weightedRegression.m
approxeq.m
approx_unique.m
argmax.m
argmin.m
asdemo.html
asdemo.m
asort.m
assert.m
assignEdgeNums.m
assign_cols.m
axis_pct.m
bipartiteMatchingDemo.m
bipartiteMatchingDemoPlot.m
bipartiteMatchingHungarian.m
bipartiteMatchingIntProg.m
block.m
cell2num.m
centeringMatrix.m
chi2inv.m
choose.m
collapse_mog.m
colmult.c
computeROC.m
compute_counts.m
conf2mahal.m
cross_entropy.m
dirKPM.m
div.m
draw_circle.m
draw_ellipse.m
draw_ellipse_axes.m
em_converged.m
entropy.m
exportfig.m
extend_domain_table.m
factorial.m
filepartsLast.m
find_equiv_posns.m
genpathKPM.m
hash_add.m
hash_del.m
hash_lookup.m
hsvKPM.m
hungarian.m
image_rgb.m
imresizeAspect.m
ind2subv.c
ind2subv.m
initFigures.m
installC_KPMtools.m
isemptycell.m
isposdef.m
isscalar.m
isvector.m
is_psd.m
is_stochastic.m
junk.c
loadcell.m
logb.m
logdet.m
logsum.m
logsumexp.m
logsumexpv.m
logsum_simple.m
logsum_test.m
marginalize_table.m
marg_table.m
matprint.m
max_mult.c
max_mult.m
mexutil.c
mexutil.h
mkdirKPM.m
mk_multi_index.m
mk_stochastic.m
montageKPM.m
montageKPM2.m
montageKPM3.m
mult_by_table.m
myintersect.m
myismember.m
myones.m
myplot.m
myrand.m
myrepmat.m
myreshape.m
mysetdiff.m
mysize.m
mysubset.m
mysymsetdiff.m
myunion.m
nchoose2.m
ncols.m
nonmaxsup.m
normalise.m
normaliseC.c
normalize.m
nrows.m
num2strcell.m
optimalMatching.m
optimalMatchingTest.m
partitionData.m
partition_matrix_vec.m
pca_kpm.m
pca_netlab.m
pick.m
plotBox.m
plotColors.m
plotcov2.m
plotcov3.m
plotgauss1d.m
plotgauss2d.m
plotgauss2d_old.m
plotROC.m
plotROCkpm.m
plot_axis_thru_origin.m
plot_ellipse.m
plot_matrix.m
plot_polygon.m
polygon_area.m
polygon_centroid.m
polygon_intersect.m
previewfig.m
process_options.m
rand_psd.m
README.txt
rectintC.m
rectintLoopC.c
rectintSparse.m
rectintSparseC.m
rectintSparseLoopC.c
repmatC.c
rgb2grayKPM.m
rnd_partition.m
rotate_xlabel.m
safeStr.m
sampleUniformInts.m
sample_discrete.m
setdiag.m
set_xtick_label.m
set_xtick_label_demo.m
softeye.m
sort_evec.m
splitLongSeqIntoManyShort.m
sprintf_intvec.m
sqdist.m
strmatch_multi.m
strmatch_substr.m
strsplit.m
subplot2.m
subplot3.m
subsets.m
subsets1.m
subsetsFixedSize.m
subv2ind.c
subv2ind.m
sumv.m
suptitle.m
unaryEncoding.m
wrap.m
xticklabel_rotate90.m
zipload.m
zipsave.m
readme_verysource.com.txt
VIP VIP
0.181633s