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High Dimensional Data Clustering (HDDC)

version 1.0.0.0 (49.1 KB) by Charles Bouveyron
The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers f

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Updated 28 Aug 2007

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The High Dimensional Data Clustering (HDDC) toolbox contains an efficient unsupervised classifiers for high-dimensional data. This classifier is based on Gaussian models adapted for high-dimensional data.

Reference: C. Bouveyron, S. Girard and C. Schmid, High-Dimensional Data Clustering, Computational Statistics and Data Analysis, to appear, 2007

Comments and Ratings (8)

khashayar

Hello,

Could you please provide a step by step direction for using this package (includes compiling part). I tried to use it, but it couldn't find hddc_learn_fast function.

Thanks,
Khashayar

Vladislavs

Under Mac with Matlab R2014a you can easily compile the MEX files with a command:
mex -llapack -lblas {mexfile}

Make sure that Xcode is installed.

ondrej

volkan

Hi,
First, thank you for the software.
Are there any solution to run this file under windows 7 or xp?
Thanks...

To compile on OS X I used
mex -lblas -lmwlapack hddc_learn.c

Alberto

Hi,

First, Thank you for posting the software!

I am experiencing the same problems compiling the C code on windows XP with lcc compiler.

Under windows I modified the code until it compiled, also linking manually BLAS and LAPACK needed libraries from <matlab>/external/lib/
---------
mex hddc_learn_fast.c C:\Matlab_R2008B\extern\lib\win32\lcc\libmwlapack.lib C:\Matlab_R2008B\extern\lib\win32\lcc\libmwblas.lib
----------
Anyways, it is a much better idea to try another compiler like Visual C++.

Regards,

I was wondering if you had a Windows version of your .c and .mexglx files. I'm having issues converting it to .mexw32. I tried mex hddc_learn_fast.c but come up with 15 errors and 2 warnings that prohibit me from compiling the file.
Thanks!

anna webster

Hi,
I couldn't use this toolbox, it can't find hddc_learn_fast function. Plz help me. Thanks

MATLAB Release Compatibility
Created with R2006a
Compatible with any release
Platform Compatibility
Windows macOS Linux