⑴ 怎麼利用r語言做em演算法估計混合雙參數指數分布的數值模擬
建議你先看一下這本書:
Modeling Survival Data Using Frailty Models
chap 2. Some Parametric Methods
2.1 Introction . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.2 Exponential Distribution . . . . . . . . . . . . . . . . . . . 20
2.3 Weibull Distribution . . . . . . . . . . . . . . . . . . . . . 21
2.4 Extreme Value Distributions . . . . . . . . . . . . . . . . 23
2.5 Lognormal . . . . . . . . . . . . . . . . . . . . . . . . . . 25
2.6 Gamma . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.7 Loglogistic . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.8 Maximum Likelihood Estimation . . . . . . . . . . . . . 30
2.9 Parametric Regression Models
chap 6. Estimation Methods for Shared Frailty Models
6.1 Introction . . . . . . . . . . . . . . . . . . . . . . . . . 105
6.2 Inference for the Shared Frailty Model . . . . . . . . . . 106
6.3 The EM Algorithm . . . . . . . . . . . . . . . . . . . . . . . 108
6.4 The Gamma Frailty Model . . . . . . . . . . . . . . . . . . . 110
6.5 The Positive Stable Frailty Model . . . . . . . . . . . . . . 111
6.6 The Lognormal Frailty Model . . . . . . . . . . . . . . . . . 113
6.6.1 Application to Seizure Data . . . . . . . . . . . . . . . 113
6.7 Modified EM (MEM) Algorithm for Gamma Frailty Models 114
6.8 Application
然後用最基本的package "survival"
並參考你的模型可能用到的一些functions:
survreg(formula, data, weights, subset,na.action, dist="weibull",....)
survreg.distributions include "weibull", "exponential", "gaussian",
"logistic","lognormal" and "loglogistic"
frailty(x, distribution="gamma", ...)
distribution: either the gamma, gaussian or t distribution may be specified.
frailty.gamma(x, sparse = (nclass > 5), theta, df, eps = 1e-05,
method = c("em","aic", "df", "fixed"),...)
⑵ R語言有沒有做CRF或者「命名實體識別」的包
基本上需要rule-based + ML-based 方法。
規則就要根據實際數據來設計了。如果有標注數據，那麼我想應該可以EM演算法學出一些對齊信息來（word alignment）。
⑶ 急求如何用MATLab實現EM演算法
最大期望演算法（Expectation Maximization Algorithm，又譯期望最大化演算法），是一種迭代演算法，用於含有隱變數（hidden variable）的概率參數模型的最大似然估計或極大後驗概率估計。
實現代碼如下：
02 Jul 2015 hui cheng
06 May 2015 Mei Dong
very good job！
12 Nov 2014 Jobaer
please, sir , send me a source code on image segmentation. I want to segement weeds from soil.My email address is [email protected] .
18 Jan 2014 HuangJunFeng HuangJunFeng
16 Dec 2013 widdy
19 Feb 2013 Tong Chu
01 Jan 2013 manas nag
sir
after executing this it is declaring that k is undefined
04 Dec 2012 Jason Rebello
Some people want to know how to view the segmented image. For example suppose you have two classes ie k=2; us the following code to view it
[row col] = size(ima);
final_img = zeros(row,col);
for i=1:row
for j=1:col
if mask(i,j)==1
final_img(i,j)=1;
else
final_img(i,j)=255;
end
end
end
imshow(final_img/255);
This is a naive way of viewing it .. you may have to change somethings if k>2. Anywayz hope it helps. The mask basically stores the segmented image.
16 Nov 2011 surya
great job.i am using the same algorithm in my project for x-ray images.can u please tell how to view the segmented image
Comment only
18 Feb 2010 prashanth
Sir, I am starting my project on the same subject. i was unable to find the algorithm psuedocode for em algorithm. kindly send me one at [email protected]. Also can u just tell me the explanation for the source code..
Comment only
21 Dec 2009 maria
Hi, could you please explain how I can use "mask" to see result of segmentation??
Comment only
17 Mar 2009 Patrick
Greetings Prof., Very nice .. could you please let me know what exactly does the mask variable store ? As what i see it classifies each pixel that falls within each class . Am i correct in that assumption?
Thanks
24 May 2008 darko brajicic
great job!
27 Apr 2008 Bilo Bilo
Thanks
15 Aug 2007 smiled fisher
06 Nov 2006 Karthik Raja T
HI, Greetings,can it for my color image segmentation ?
04 Sep 2006 Mikel Rodriguez
12 Jul 2006 carlos mas
03 May 2006 Mohamed Sami
look when u make a code u must show us the output to see it then u read ur code .. try to explain that with output we can see bye
⑷ matlab實現EM演算法
1. EM演算法程序：
http://www.mathworks.com/matlabcentral/fileexchange/3713-em-algorithm-for-clustering-emfc-m
2. EM image segmentation：
http://www.mathworks.com/matlabcentral/fileexchange/10956-em-image-segmentation
3. 貝葉斯圖像分割程序：(Bayseian image segmentation)
沒有找到合適的程序代碼 :-(
⑸ 求MATLAB 編寫的支持向量機、神經網路、KNN或EM演算法有關「數據缺失」的源程序滿意最少在加100分。謝謝！！
好像這些演算法在數據缺失的情況下是沒法進行的吧，只能說改進之後在數據缺失情況下做了相應處理，你說的這些演算法都可以在網上找到代碼