% In this example a support vector regression algorithm is trained on a
% real-valued toy data set. The underlying library used for the SVR training is
% LIBSVM. The SVR is trained with regularization parameter C=1 and a gaussian
% kernel with width=2.1.
% 
% For more details on LIBSVM solver see http://www.csie.ntu.edu.tw/~cjlin/libsvm/ .

% LibSVR
print LibSVR
set_kernel GAUSSIAN REAL 10 2.1
set_features TRAIN ../data/fm_train_real.dat
set_labels TRAIN ../data/label_train_regression.dat
new_regression LIBSVR
svr_tube_epsilon 1e-2
c 0.017

train_regression

set_features TEST ../data/fm_test_real.dat
out.txt = classify
! rm out.txt
