perClass

Index out of bounds in sdsvc

2012-01-31T22:25:13+01:00

Hi,
training sdsvc with default settings on a particular dataset I obtain as follows:

??? Error using ==> ind2code at 8
Index out of bounds.

Error in ==> ..perClass_Demoperclass@sddatasubset.p>subset at 73

Error in ==> ..perClass_Demoperclass@sddatasubsref.p>subsref at 31

Error in ==> ..perClass_Demoperclasssdsvc.p>sdsvc at 210

Error in ==> ..perClass_Demoperclass@sdpplapply_untrained.p>apply_untrained at 150

Error in ==> ..perClass_Demoperclass@sdpplmtimes.p>mtimes at 72

Error in ==> par_classify_BR at 20
    trainedSvc=trainngData*untrainedSvc;

Could you please help with the problem?

Thanks in advance.
Tomasz

sdparzen maxsamples

2012-02-01T10:24:24+01:00

Hi,

When using the ‘maxsamples’ option for the sdparzen classifier, how are the training samples chosen? Is this completely random?

Best regards,
Davy

sdimage label transparency

2012-01-30T16:26:26+01:00

Hi,

When showing image data using the sdimage function, one can set the label transparency to “very transparent” using the GUI. Is it also possible to set this property automatically in the code itself?

Cheers,
Davy

Center of SVDD

2012-01-24T22:20:09+01:00

Is there any ways to find the center of SVDD using Gaussian kernel ?

bug in fixedcc.m

2012-01-17T14:49:16+01:00

Hi,

Line 204 in fixedcc.m function :
par - w.data{4};

Should it be replaced by ?
par = w.data{4};

Thank you for your help.

Internal error in sdtree

2012-01-13T17:57:08+01:00

Please help figure out what is the problem.

>> sdtree(ds)
??? Error using ==> perclass_mex
Tree training: Internal error

Error in ==>
C:DocumentsNaukaResearchEnvPerClassperClass_Demoperclasssdtree.p>sdtree at
181

I am using:
perClass Demo 3.1.2 (22-Dec-2011), Copyright (C) 2007-2011, PR Sys Design, All rights reserved

Regards.

PRTools Version 4.2.1 does not seem to contain the mapping class definition file.

2012-01-02T16:19:53+01:00

Hi,

I had the previous version of PRTools and tried to install the newer version (4.2.1) instead.

However, I was not able to find the mapping.p and mapping.m file with the newer version. I remember having it in the previous version.

The ‘Contents.m’ file in the newer version mentions the file. I downloaded the zip file containing the codes twice and tried. Is there any step of the installation that I am missing?

Thanks!

ROC questions

2011-12-14T09:30:50+01:00

Hi,

I have 2 questions regarding ROC analysis in perClass:

(1) When I use sddecide to create an operating point using the weighting-based option (‘w’), is there a way to retrieve the actual operating point (e.g. to mark it in the ROC curve)?

(2) [Probably this is very simple, but I cannot seem to find it] When doing the ROC analysis, how can I choose the operating point that minimizes the overall classification error (not the operating point that minimizes the per-class classification errors)?

Cheers,
Davy

what exactly svc returns?

2011-12-11T12:14:27+01:00

Hi dear forum members,
I’m new in this forum and in PRTools too and I have been a little bit confused . :-S
Let Atrn be my train data which has: 100 objects by 2 features with 2 classes: [50 50] and Atrn be my testing data: 100 objects by 2 features with 2 classes: [50 50] .
I want to create and train a classifier combiner using a membership matrix U (100x2) with soft clustering weights calculated using trained SOM,so I wrote the following code in order to create and train the combiner:

NumOfClassifiers=5;

for clf=1:NumOfClassifiers

Wsvm{clf}=svc();
Wsvmtrn{clf}=Atrn*Wsvm{clf};
str_Wsvmtrn=struct(Wsvmtrn{clf});
SupportVectorIndices=Wsvmtrn{clf}.data{5};
Wsvmtrn{clf}.data{2}.data=Usom(SupportVectorIndices,:); % include U here ????
end

From the workspace I saw that the data field of the struct str_Wsvmtrn is a 1x5 cell : The Wsvmtrn.data{5} field is a 42x1 vector which represent the support vector indices and Wsvmtrn.data{3} field is a 43x1 vector which represent the weights (but why 43x1 and not 42x1 ?).As for the fields Wsvmtrn.data{1} (1x2 vector) and Wsvmtrn.data{2} ( a 42 by 2 data with 2 classes: [21 21]) ,what exactly do they represent? I thought that the Wsvmtrn.data{2} could be those Trainset’s objects that are pointed by the 42
support vector indices(as they have the same dimensionality) but the values aren’t the same!Please help me!I have no idea!

From the 100 weights of the membership matrix , I take the 42 which corresponds to the 42 support vector indices and now I want to update the struct str_Wsvmtrn with them.But I don’t know how.

Any response will be appreciated.
Thanks a lot.

Modifications of dd_tools’ simpleroc

2011-11-24T11:41:48+01:00

Hello,
i have made some modifications to simpleroc of dd_tools. I think they might be useful for others.

1) I have changed the branch that handles the “not uniquely defined ROC”. I have replaced the find (linear search on the whole vector) to a smaller loop, exploiting the fact that the thresholds are sorted.

The code is much faster now. With 10000 objects of which 86288 are unique, these are the timings on my computer:
- original 15 secs
- modified 0.33 secs

2) I have added a threshold to the end of threshold vector in order to be of the same size of f (errors).
Assume you have 10 thresholds, currently the tenth threshold thr(10) corresponds to objects having “posterior probability” GREATER EQUAL (right?) than that threshold (the number is stored in f(10)). Since this is the last threshold, the ≥ is satisfied only by one object and as strict equality.

f(11) is about all object reject by the classifier.
Adding this line:


uout = [uout; uout(end)+10*eps(uout(end))];

You will a have a u(11) greater than u(10). This threshold will be strictly greater than any posterior probability generated, so all object are rejected at this threshold (in accordance with f(11))

the modified file is attached. Let me know what you think about.

Bye,
Giuseppe