RJ Honicky
In the most recent release of Maemo, there is no FORTRAN compiler, due to a switch from the ARM to ARMEL architecture between os2007 and os2008. Since Debian does not currently support FORTRAN on ARMEL, neither does Maemo. However, recent unstable releases of Debian do have a FORTRAN compiler (gfortran). Therefore, we should be able to use a FORTRAN compiler with some minimal package work.
Numpy, or NUMerical PYthon, wraps several FORTRAN libraries for matrix manipulation and numerical computation. Unfortunately, some of these libraries need to be tweeked to each fortran compiler, so there we can't just compile the fortran into C and then compile with GCC. Thus, to get the whole Numpy suite running, gfortran will need to be working.
There is, however, an older version of Numpy, called Numeric, available as 'python-numeric', which can be fetched with
apt-get install python-numeric
also, we need python 2.5, which can be installed with
apt-get install python2.5
Support Vector Machines (SVM) are a common tool in statistical machine learning for numerically efficient classification of vectors into discreet classes, and doing regression (SVR).
I have built and and packaged libsvm, a common and robust tool with python bindings. It is available under the class repository. You can get it by doing:
apt-get install libsvm-python
after adding the class repository to your sources.list file:
http://phone.cs.berkeley.edu/apt
To train and develop your model, download the package at http://www.csie.ntu.edu.tw/~cjlin/cgi-bin/libsvm.cgi?+http://www.csie.ntu.edu.tw/~cjlin/libsvm+tar.gz or install scipy on your desktop for a robust, pre-packaged python binding. Do
import sandbox.svm.libsvm
or the other classes. There is good documentation at http://cours-info.iut-bm.univ-fcomte.fr/docs/python/scipy/scipy.sandbox.svm-module.html