Hi. In this package, I did not include different features selection techniques. I will submit another package in the next month that includes about 4-5 feature selection methods. Meanwhile, some of them are already available in MatlabFileExchange (not by me! )
the following code is easier and faster:
X_hist=sum(image,1);
Y_hist=sum(image,2);
X=1:N; Y=1:M;
centX=sum(X.*X_hist)/sum(X_hist);
centY=sum(Y'.*Y_hist)/sum(Y_hist);
Besides, you may use "meshgrid" command instead of defining x variable in your code (i.e. x=meshgrid(1:columns,1:rows);)
09 May 2011
Random Forest
Creates an ensemble of cart trees similar to the matlab TreeBagger class.
Author: Leo
Thanks Leo
I got another error using your codes:
??? Error: File: cartree.m Line: 50 Column: 25
Expression or statement is incorrect--possibly unbalanced (, {, or [.
Error in ==> Stochastic_Bosque at 46
Random_ForestT = cartree(Data(TDindx,:),Labels(TDindx), ...
The 50th line is:
[unique_labels,~,Labels]= unique(Labels);
It seems odd; at least for me.
Besides, I wanna know that your code is based on Random subspace method? If so, how many percent of features is used to create feature subsets?
09 May 2011
Random Forest
Creates an ensemble of cart trees similar to the matlab TreeBagger class.
Author: Leo
Thanks Leo
I got another error using your codes:
??? Error: File: cartree.m Line: 50 Column: 25
Expression or statement is incorrect--possibly unbalanced (, {, or [.
Error in ==> Stochastic_Bosque at 46
Random_ForestT = cartree(Data(TDindx,:),Labels(TDindx), ...
The 50th line is:
[unique_labels,~,Labels]= unique(Labels);
It seems odd; at least for me.
Besides, I wanna know that your code is based on Random subspace method? If so, how many percent of features is used to create feature subsets?
28 Apr 2011
Random Forest
Creates an ensemble of cart trees similar to the matlab TreeBagger class.
Author: Leo
Hi Leo
When I run this command:
Random_Forest = Stochastic_Bosque(Patterns,Targets);
I get this error:
??? Undefined variable "internal" or class "internal.stats.getargs".
Error in ==> Stochastic_Bosque at 39
[eid,emsg,minparent,minleaf,m,nTrees,n,method,oobe,W] =
internal.stats.getargs(okargs,defaults,varargin{:});
Hi. In this package, I did not include different features selection techniques. I will submit another package in the next month that includes about 4-5 feature selection methods. Meanwhile, some of them are already available in MatlabFileExchange (not by me! )
Hi. In this package, I did not include different features selection techniques. I will submit another package in the next month that includes about 4-5 feature selection methods. Meanwhile, some of them are already available in MatlabFileExchange (not by me! )
Comment only
27 Feb 2013
Ensemble Toolbox
This toolbox provides some combination methods to fuse an ensemble of classifiers
Comment only