Category: Matlab code for mutual information calculation

Matlab code for mutual information calculation

16.11.2020 By Vot

By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. Cross Validated is a question and answer site for people interested in statistics, machine learning, data analysis, data mining, and data visualization.

It only takes a minute to sign up. I've been set a sample exercise by my supervisor, and I'm totally lost as to where I should be heading. Then, I'm meant to shift the means of the histograms so that they overlap to some extent, and then calculate the drop in mutual information. I've tried a variety of solutions, but none have given me reliable results so far.

What I'm now trying to do is calculate the entropy of each of the histograms, and subtract the entropy of the joint histogram. However, even this is becoming difficult. From my albeit limited understanding of information theory, the above should have calculated the information "contained" within the first and second histograms, and summed them. I would expect a value of 1 for this sum, and I do indeed achieve this value. However, what I'm stuck on now is determining the joint histogram, and following from that, the joint entropy to subtract.

Is the prob2D matrix I've created the joint probability?? If so, how can I use this?? Any insight or links to relevant papers would be much appreciated - I've been googling quite a bit, but I haven't been able to turn up anything of value. Plotting the independence assumed distribution and the joint distribution side by side shows how similar they are:.

If, on the other hand, we introduce dependence by generating randpoints2 to have some component of randpoints1like this for example:. Plotting the above distributions again shows a clear would be clearer with more points and bins of course difference between joint pmf that assumes independence and a pmf that's generated by sampling the variables simultaneously.

It had many informative references and it provided useful Python code supporting their explanations. The code that they provided used the numpy. You can very easily modify it to display the histograms that you need then use the MI as needed. The code and references that they provided as also very enlighting. You might also benefit from their explanation and use of code to calculate KL Divergence.

I find this post, along with the explanation and code provided in the first answer above when combined, to offer a very interesting solution. Sign up to join this community. The best answers are voted up and rise to the top. Home Questions Tags Users Unanswered. Calculating the mutual information between two histograms Ask Question.

Asked 5 years, 7 months ago. Active 9 months ago. Viewed 5k times. Jack Jack 1 1 silver badge 3 3 bronze badges. Active Oldest Votes.

Alexander F. Your answer was very helpful, I'll award you with the bounty! I believe that you can increase the number of bins and points to get a better approximation of the continuous case.Updated 23 Aug This package has also been used for general machine learning and data mining purposes such as feature selection, Bayesian network construction, signal processing, etc. Another related package for minimal redundancy feature selection is also available at the Matlab Central exchange site, under the category of "Biotech and Pharmaceutical".

In short, this package is free to non-profit use but cannot be re-distributed in any form, including revised forms, without the explicit permission for the author, Hanchuan Peng. See readme file for further information. Hanchuan Peng Retrieved October 12, I don't think the condmutualinfo a,c,b should be larger than the condmutualinfo a,cand I am very confused about this.

I'll appreciate if anyone can explain it for me. So a straightforward workaround would be to normalize the features before using the mrmr function this worked for me, however, would be interesting to know the authors' opinion about this odd behaviour of the code. I did eveything in commnets.

But I am also getting below error again. Could you help me please? Error using estpab Requested x21 See array size limit or preference panel for more information. Open "miinclude. Open "estjointentropy. Thanks for sharing your great work. Can you please let me know if there is any way of using your algorithm to calculate MI in 2 images with slightly size difference?

I am getting the error: Undefined function or variable 'estpab'. Hi When I run the makeosmex. Anyone can help me, please? But the question is which mechanism was the basis of the probability calculation.

Erdem Isenkul proposed a practical and useful way. It says that it does not have enough input parameters.

I need help resolving this. My values are not integers. How can I use your function? I want to explain the dependence between acceleration and emissions. Since I have acceleration, I have negative values too.

If you get an error using the functions here is the solution; First of all you need to "mex" all of.Updated 10 Jun MI is a good approach to align two images from different sensor. Here is a function with the simplest form to calculate the mutual information between two images. HU xb Retrieved October 12, However, I think that the function can be optimized to speed up calculations. I have identified two such code portions.

I think that there is a little mistake at the end of that function. Hi; Thank you HU xb very much for your code ,I have a problem my images are grayscale 32 bits '. Learn About Live Editor. Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select:. Select the China site in Chinese or English for best site performance. Other MathWorks country sites are not optimized for visits from your location.

Toggle Main Navigation. File Exchange. Search MathWorks. Open Mobile Search. Trial software. You are now following this Submission You will see updates in your activity feed You may receive emails, depending on your notification preferences. Follow Download. Overview Functions. Cite As HU xb Comments and Ratings 6. Irene Belik 1 May Hi : it is not working if I have normalized images with the function mat2graywhat can I do? Muzammil 2 Apr HUxb, great work. Jorge 3 May Eyal David 13 Mar Hi, I think that there is a little mistake at the end of that function.

Soum 8 Aug Tags Add Tags image registration joint histogram mutual information shannon entropy. Discover Live Editor Create scripts with code, output, and formatted text in a single executable document.Sign in to comment. Sign in to answer this question. Unable to complete the action because of changes made to the page. Reload the page to see its updated state. Choose a web site to get translated content where available and see local events and offers.

Based on your location, we recommend that you select:. Select the China site in Chinese or English for best site performance.

Other MathWorks country sites are not optimized for visits from your location. Toggle Main Navigation. Search Answers Clear Filters. Answers Support MathWorks. Search Support Clear Filters. Support Answers MathWorks.

Search MathWorks. MathWorks Answers Support. Open Mobile Search. Trial software. You are now following this question You will see updates in your activity feed. You may receive emails, depending on your notification preferences. Pairwaise Mutual Information Calculation.

Marimuthu Ananthavelu on 23 Dec Vote 0. Edited: Marimuthu Ananthavelu on 24 Dec I am trying to estimate the Mutual Information for pairwise combinations for the whole matrix which is an EEG data. I use the functions defined here link. And I use following code to estimate this pairwise. Image Analyst on 24 Dec Cancel Copy to Clipboard. Make it easy for people to help you, not hard, by attaching whatever filename "data" is with the paperclip icon.

By the way, it's not a good idea to have "data" be both the filename string used in load, and the numerical data variable. For example since "data" is the filename. Marimuthu Ananthavelu on 24 Dec Sorry for that confusion.Updated 07 Mar Mo Chen Retrieved October 12, Comming the same problem which Maksim : who knows why nmi randi ,1,1e3 ,randi ,1,1e3. They're different series of numbers, so how they share similar information?

Can any one tell me maximum possible value must achieve according to simulation based for these tests. In the conditional entropy, you cannot calculate the joint distribution from marginal distributions. The joint distribution should be one of the arguments of the function. I don't think either of the proposed solutions provided by Francesco and Subash are correct. If you have. The original code does, whereas Francesco's change doesn't. So simply reversing the order is incorrect.

The underlying error is that the code expects x and y to be positive integers. Rounding a continuous variable will mean that you have valid indexes except if the input has a value that rounds to zero. However, you could consider this as being analogous to binning the data, except that if multiple points go into the same bin, that bin will only ever have a value of 1.

So I suspect Subash's suggestion also invalidates the calculation. The real answer is actually provided by the author in the package description: "This toolbox contains functions for discrete random variables". A different approach must be used if one or both of the variables is continuous.

Hey guys, regarding sparse function error, which answer is correct of the below as answered by francesco and subash Is the output of the conditionalEntropy function a normalized value?

I had got values of conditional Entropy to be greater than 1, which was expected. Very useful and efficient toolbox, thank you. However, there is a bug in the nmi. But this is obvious a typo, so it does not influence my rating. Learn About Live Editor. Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select:.

Select the China site in Chinese or English for best site performance.

matlab code for mutual information calculation

Other MathWorks country sites are not optimized for visits from your location. Toggle Main Navigation. File Exchange. Search MathWorks. Open Mobile Search. Trial software. You are now following this Submission You will see updates in your activity feed You may receive emails, depending on your notification preferences. Information Theory Toolbox version 1. Functions for Information theory, such as entropy, mutual information, KL divergence, etc.Sign in to comment. Sign in to answer this question.

Unable to complete the action because of changes made to the page. Reload the page to see its updated state. Choose a web site to get translated content where available and see local events and offers.

[BayesGroup Seminar]: On Mutual Information Estimation

Based on your location, we recommend that you select:. Select the China site in Chinese or English for best site performance. Other MathWorks country sites are not optimized for visits from your location. Toggle Main Navigation. Search Answers Clear Filters. Answers Support MathWorks. Search Support Clear Filters. Support Answers MathWorks. Search MathWorks.

matlab code for mutual information calculation

MathWorks Answers Support. Open Mobile Search. Trial software. You are now following this question You will see updates in your activity feed. You may receive emails, depending on your notification preferences. Mutual information between two vectors by using Histograms. Shirin Dezfool on 31 May Vote 0. Commented: ahmed silik on 14 Aug Accepted Answer: HU xb.

I have two auto-correlated vectors two vector which are simulated as network traffic and I want to see how much are they correlated to each other by using Mutual information. First I must find the histograms and then mutual information. I am searching for a code like that but for vectors. Is there any?Updated 03 Jan Note 2: Requires the 'Entropy' and 'JointEntropy' functions. Will Dwinnell Retrieved October 12, I think there is something wrong! Clearly wrong results!

Can this code generate a mutual information matrix for each feature column to every other feature column? Those who cannot find Entropy. These files ara available there, by the same author.

The Mutual Information does not seem to run without these functions. I ran the following and got the answers below.

Pairwaise Mutual Information Calculation

Does not seem right to me. A and B are completely independent random numbers, which I verified. Learn About Live Editor. Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select:. Select the China site in Chinese or English for best site performance. Other MathWorks country sites are not optimized for visits from your location.

Toggle Main Navigation. File Exchange. Search MathWorks. Open Mobile Search. Trial software. You are now following this Submission You will see updates in your activity feed You may receive emails, depending on your notification preferences.

Subscribe to RSS

Mutual Information version 1. Calculates the mutual information between two discrete variables or a group and a single variable. Follow Download. Overview Functions. Cite As Will Dwinnell

matlab code for mutual information calculation