How to manually construct or modify a cross-validation object in MATLAB?

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Vilmantas Gegzna
Vilmantas Gegzna 2015 年 4 月 14 日
コメント済み: Rik 2021 年 3 月 29 日
Short question:
I want your help to manually construct or modify Matlab cross-validation (CV) object created using function cvpartition when it's known which observations belong to training and which to validation partitions.
Extended question:
I have a kind of specific dataset in which several observations (each represented by a separate row) belong to the same object of investigation (e.g. measurements of the same object were performed several times). Each object (and it's observation) belongs to a certain class (e.g. yellow object, green object, etc.) as well. The problem is this: it's needed a CV object in which all observations of the same object belong to the same (either training or validation) partition as a block of data (unfortunately I'm not sure how to implement this) and the data would be distributed to partitions in stratified way (luckily, this is implemented in function cvpartition). I tried to access indices of CV object (cvo.indices) but they are locked. Here cvo is:
cvType = 'kfold';
nPartitions = 5;
cvo = cvpartition(my_classes,cvType,nPartitions);
Your insights and ideas how to construct or modify cvo manually are welcomed.
  2 件のコメント
Rik 2021 年 3 月 29 日
Comment posted as flag by patrck rich:
the solution is no longer working in recent versions
That is always a risk when trying to modify internal files. However, I ran the lines below in the online interface (I cleared the output, as I don't expect Mathworks would be happy with me sharing their files..)
OS={'Windows','macOS','Linux'};fprintf('This is version %s, running on %s.',version,OS{[ispc ismac isunix&&~ismac]})
This is version (R2021a), running on Linux.
As far as I can judge from the code I can read, I don't see a reason why it wouldn't still work, but feel free to post a comment explaining which exact steps you took and which lines you modified.



Vilmantas Gegzna
Vilmantas Gegzna 2015 年 4 月 22 日
編集済み: Vilmantas Gegzna 2015 年 4 月 22 日
I found, that I can modify the cross-validation object (CVO) which class is cvpartition by modifying several lines in cvpartition.m file from:
properties(GetAccess = 'private', SetAccess = 'private')
properties(GetAccess = 'public', SetAccess = 'public')
This allowed me to modify indices of CVO manually.
I wonder if there are any other way to set indices of CVO without changing the lines in cvpartition.m? This is the case when I want to run Matlab on my campus computer.
  2 件のコメント
Sergio Gutierrez
Sergio Gutierrez 2018 年 8 月 11 日
I have done the same modification as Albert Sama said in the below comment. You require administrative rights to make changes. I used Notepad++ in administrator mode.


その他の回答 (3 件)

Jo 2016 年 11 月 4 日
It seems that one year later your solution is not working anymore, maybe they changed the function.
Indeed, I tried to modify as you suggested "properties(GetAccess = 'public', SetAccess = 'public')", but it only allows me to access to the number of observations and not the indices. Indices are created by "methods" defined in cvpartition.m (test, training). And I do not understand how to change these to choose my own indices.
Maybe if you have progessed in all that since you first posted your question.... I would be really greatful to have some help in there.
Using random crossvalidation is of none interest for me, I need to choose the block myself to have a more robust solution. Thanks to anyone that can help me!!!
  2 件のコメント
Evelyn Tang
Evelyn Tang 2018 年 11 月 9 日
This is wonderful and just what I need, thank you so much! Works perfectly :)


Roberto Herrera-Lara
Roberto Herrera-Lara 2015 年 4 月 14 日
try to do this
  1 件のコメント
Vilmantas Gegzna
Vilmantas Gegzna 2015 年 4 月 22 日
編集済み: Vilmantas Gegzna 2015 年 4 月 22 日
Thank you, Roberto, your link provided an extremely good description of k-fold cross-validation and updated my knowledge. Unfortunately, I was searching for a bit different thing.


John Smith
John Smith 2018 年 11 月 21 日
Two small additions:
2.Restart Matlab after that


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