Re: [External] - Re: MultivariateNormalMixtureExpectationMaximization only 1 dimension

2024-03-04 Thread Craig Brautigam 

Yes thank you!  As you stated you should be able to have a single column with n 
components (having enough data samples of course).. Having your fix would  
allow me to port this code over from what I see.

Thx!



From: Alex Herbert 
Sent: Monday, March 4, 2024 5:06 PM
To: Commons Users List 
Subject: [External] - Re: MultivariateNormalMixtureExpectationMaximization only 
1 dimension

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Hi,

I think this is a bug in the
MultivariateNormalMixtureExpectationMaximization class. When I update the
code to allow 1 column in the rows it outputs a similar fit to matlab.
Here's an example of Matlab:

X = [normrnd(0, 1, 100, 1); normrnd(2, 2, 100, 1)]
GMModel = fitgmdist(X,2);

>> GMModel.mu
ans =
0.0737
3.0914
>> GMModel.ComponentProportion
ans =
0.67500.3250
>> GMModel.Sigma
ans(:,:,1) =
1.0505
ans(:,:,2) =
1.6593

I pasted the same X data into a test for
MultivariateNormalMixtureExpectationMaximization that had been updated to
allow data with a single column and get the following fit:

MultivariateNormalMixtureExpectationMaximization fitter
= new MultivariateNormalMixtureExpectationMaximization(data);

MixtureMultivariateNormalDistribution initialMix
= MultivariateNormalMixtureExpectationMaximization.estimate(data, 2);
fitter.fit(initialMix);
MixtureMultivariateNormalDistribution fittedMix = fitter.getFittedModel();
List> components =
fittedMix.getComponents();

for (Pair component : components) {
final double weight = component.getFirst();
final MultivariateNormalDistribution mvn = component.getSecond();
final double[] mean = mvn.getMeans();
final RealMatrix covMat = mvn.getCovariances();
System.out.printf("%s : %s : %s%n", weight, Arrays.toString(mean),
covMat.toString());
}

0.6420433138817465 : [0.016942587744259194] :
Array2DRowRealMatrix{{0.9929681356}}
0.3579566861182536 : [2.9152176347671754] :
Array2DRowRealMatrix{{1.8940290549}}

The numbers are close enough to indicate that the fit is valid.

I think the error has been in assuming that because you require 2
components to have a mixture model then you must have 2 columns in the
input data. However this is not true. You can fit single dimension data
with a mixture of single Gaussians.

Is this the functionality that you are expecting?

Regards,

Alex


On Mon, 4 Mar 2024 at 20:48, Craig Brautigam 
wrote:

> Forgive me if this comes in twice... I did not subscribe first before
> sending the message below.
>
>
> 
> From: Craig Brautigam
> Sent: Monday, March 4, 2024 1:33 PM
> To: user@commons.apache.org 
> Subject: MultivariateNormalMixtureExpectationMaximization only 1 dimension
>
> Hi,
>
> Full disclosure, I'm not a mathematician so I can not go into the weeds
> into the math.  However I am tasked with porting some matlab code that is
> doing gaussian mixed model to java.  I really want to use apache common
> math if possible.  However the code that I'm porting has 1 dimension ( a
> single variable/attribute/property) that GMMs are being created from.
>
> MultivariateNormalMixtureExpectationMaximization looks to be a pretty
> close drop in replacement for the matlab functions
> https://usg02.safelinks.protection.office365.us/?url=https%3A%2F%2Fwww.mathworks.com%2Fhelp%2Fstats%2Ffitgmdist.html=05%7C02%7Ccbrautigam%40icr-team.com%7C66844f07674e412ff28f08dc3ca845eb%7C3d860a84424d44f9ab2bc61a036b4904%7C0%7C0%7C638451940630725298%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C=XjMm%2FRepVwQdEtNTzDEAu0xxltECt6plR2sLXmt3Q44%3D=0<
> https://usg02.safelinks.protection.office365.us/?url=https%3A%2F%2Fwww.mathworks.com%2Fhelp%2Fstats%2Ffitgmdist.html=05%7C02%7Ccbrautigam%40icr-team.com%7C66844f07674e412ff28f08dc3ca845eb%7C3d860a84424d44f9ab2bc61a036b4904%7C0%7C0%7C638451940630725298%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C=XjMm%2FRepVwQdEtNTzDEAu0xxltECt6plR2sLXmt3Q44%3D=0>
>  andhttps://
> https://usg02.safelinks.protection.office365.us/?url=http%3A%2F%2Fwww.mathworks.com%2Fhelp%2Fstats%2Fgmdistribution.html=05%7C02%7Ccbrautigam%40icr-team.com%7C66844f07674e412ff28f08dc3ca845eb%7C3d860a84424d44f9ab2bc61a036b4904%7C0%7C0%7C638451940630725298%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C=dxjQmvgLCqoDqbPh3ZDybn%2FZkOGfd0cKfT73xhK5upc%3D=0,
>  however the constructor
> for

Re: MultivariateNormalMixtureExpectationMaximization only 1 dimension

2024-03-04 Thread Alex Herbert 
Hi,

I think this is a bug in the
MultivariateNormalMixtureExpectationMaximization class. When I update the
code to allow 1 column in the rows it outputs a similar fit to matlab.
Here's an example of Matlab:

X = [normrnd(0, 1, 100, 1); normrnd(2, 2, 100, 1)]
GMModel = fitgmdist(X,2);

>> GMModel.mu
ans =
0.0737
3.0914
>> GMModel.ComponentProportion
ans =
0.67500.3250
>> GMModel.Sigma
ans(:,:,1) =
1.0505
ans(:,:,2) =
1.6593

I pasted the same X data into a test for
MultivariateNormalMixtureExpectationMaximization that had been updated to
allow data with a single column and get the following fit:

MultivariateNormalMixtureExpectationMaximization fitter
= new MultivariateNormalMixtureExpectationMaximization(data);

MixtureMultivariateNormalDistribution initialMix
= MultivariateNormalMixtureExpectationMaximization.estimate(data, 2);
fitter.fit(initialMix);
MixtureMultivariateNormalDistribution fittedMix = fitter.getFittedModel();
List> components =
fittedMix.getComponents();

for (Pair component : components) {
final double weight = component.getFirst();
final MultivariateNormalDistribution mvn = component.getSecond();
final double[] mean = mvn.getMeans();
final RealMatrix covMat = mvn.getCovariances();
System.out.printf("%s : %s : %s%n", weight, Arrays.toString(mean),
covMat.toString());
}

0.6420433138817465 : [0.016942587744259194] :
Array2DRowRealMatrix{{0.9929681356}}
0.3579566861182536 : [2.9152176347671754] :
Array2DRowRealMatrix{{1.8940290549}}

The numbers are close enough to indicate that the fit is valid.

I think the error has been in assuming that because you require 2
components to have a mixture model then you must have 2 columns in the
input data. However this is not true. You can fit single dimension data
with a mixture of single Gaussians.

Is this the functionality that you are expecting?

Regards,

Alex


On Mon, 4 Mar 2024 at 20:48, Craig Brautigam 
wrote:

> Forgive me if this comes in twice... I did not subscribe first before
> sending the message below.
>
>
> 
> From: Craig Brautigam
> Sent: Monday, March 4, 2024 1:33 PM
> To: user@commons.apache.org 
> Subject: MultivariateNormalMixtureExpectationMaximization only 1 dimension
>
> Hi,
>
> Full disclosure, I'm not a mathematician so I can not go into the weeds
> into the math.  However I am tasked with porting some matlab code that is
> doing gaussian mixed model to java.  I really want to use apache common
> math if possible.  However the code that I'm porting has 1 dimension ( a
> single variable/attribute/property) that GMMs are being created from.
>
> MultivariateNormalMixtureExpectationMaximization looks to be a pretty
> close drop in replacement for the matlab functions
> https://www.mathworks.com/help/stats/fitgmdist.html<
> https://www.mathworks.com/help/stats/fitgmdist.html> andhttps://
> www.mathworks.com/help/stats/gmdistribution.html, however the constructor
> for MultivariateNormalMixtureExpectationMaximization clearly states the the
> number of columns in the double[][]data array MUST be no less thatn2
> columns.  I'm completely baffled as to why this is the case if I want to
> try to fit data with 1 dimension in it.  Is there a workaround I can use
> like provide a dummy column of data with all 0s to pacify the constructor?
> Is there another class I should be using?
>
> Any help would be greatly appreciated.
>
> Thx!
>
>
> 
> The information contained in this e-mail and any attachments from ICR,
> Inc. may contain confidential and/or proprietary information, and is
> intended only for the named recipient to whom it was originally addressed.
> If you are not the intended recipient, any disclosure, distribution, or
> copying of this e-mail or its attachments is strictly prohibited. If you
> have received this e-mail in error, please notify the sender immediately by
> return e-mail and permanently delete the e-mail and any attachments.
>

MultivariateNormalMixtureExpectationMaximization only 1 dimension

2024-03-04 Thread Craig Brautigam 
Hi,

Full disclosure, I'm not a mathematician so I can not go into the weeds into 
the math.  However I am tasked with porting some matlab code that is doing 
gaussian mixed model to java.  I really want to use apache common math if 
possible.  However the code that I'm porting has 1 dimension ( a single 
variable/attribute/property) that GMMs are being created from.

MultivariateNormalMixtureExpectationMaximization looks to be a pretty close 
drop in replacement for the matlab functions 
https://www.mathworks.com/help/stats/fitgmdist.html
 andhttps://www.mathworks.com/help/stats/gmdistribution.html, however the 
constructor for MultivariateNormalMixtureExpectationMaximization clearly states 
the the number of columns in the double[][]data array MUST be no less thatn2 
columns.  I'm completely baffled as to why this is the case if I want to try to 
fit data with 1 dimension in it.  Is there a workaround I can use like provide 
a dummy column of data with all 0s to pacify the constructor? Is there another 
class I should be using?

Any help would be greatly appreciated.

Thx!



The information contained in this e-mail and any attachments from ICR, Inc. may 
contain confidential and/or proprietary information, and is intended only for 
the named recipient to whom it was originally addressed. If you are not the 
intended recipient, any disclosure, distribution, or copying of this e-mail or 
its attachments is strictly prohibited. If you have received this e-mail in 
error, please notify the sender immediately by return e-mail and permanently 
delete the e-mail and any attachments.

Re: MultivariateNormalMixtureExpectationMaximization only 1 dimension

2024-03-04 Thread Craig Brautigam 
Forgive me if this comes in twice... I did not subscribe first before sending 
the message below.



From: Craig Brautigam
Sent: Monday, March 4, 2024 1:33 PM
To: user@commons.apache.org 
Subject: MultivariateNormalMixtureExpectationMaximization only 1 dimension

Hi,

Full disclosure, I'm not a mathematician so I can not go into the weeds into 
the math.  However I am tasked with porting some matlab code that is doing 
gaussian mixed model to java.  I really want to use apache common math if 
possible.  However the code that I'm porting has 1 dimension ( a single 
variable/attribute/property) that GMMs are being created from.

MultivariateNormalMixtureExpectationMaximization looks to be a pretty close 
drop in replacement for the matlab functions 
https://www.mathworks.com/help/stats/fitgmdist.html
 andhttps://www.mathworks.com/help/stats/gmdistribution.html, however the 
constructor for MultivariateNormalMixtureExpectationMaximization clearly states 
the the number of columns in the double[][]data array MUST be no less thatn2 
columns.  I'm completely baffled as to why this is the case if I want to try to 
fit data with 1 dimension in it.  Is there a workaround I can use like provide 
a dummy column of data with all 0s to pacify the constructor? Is there another 
class I should be using?

Any help would be greatly appreciated.

Thx!



The information contained in this e-mail and any attachments from ICR, Inc. may 
contain confidential and/or proprietary information, and is intended only for 
the named recipient to whom it was originally addressed. If you are not the 
intended recipient, any disclosure, distribution, or copying of this e-mail or 
its attachments is strictly prohibited. If you have received this e-mail in 
error, please notify the sender immediately by return e-mail and permanently 
delete the e-mail and any attachments.

[ANNOUNCE] Apache Commons DBCP 2.12.0

2024-03-04 Thread Gary Gregory 
The Apache Commons DBCP team is pleased to announce the release of
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