Wrapper on top of libsvm-tools

Svmwrap can be used to train/test regressors using libsvm-tools.

(Scary) usage: usage: svmwrap -i <filename>: training set or DB to screen --feats <int>: number of features output file [--kernel <string>] choose kernel type {Lin|RBF|Sig|Pol} C in the loss function of epsilon-SVR; (0 <= epsilon <= max_i(|y_i|)) NLopt with MAX_ITER (global optim.) instead of grid-search (recommended: MAX_ITER >= 100) gamma (for RBF and Sig kernels) r for the Sig kernel ON instance-wise-normalization ON [0:1] scaling (NOT PRODUCTION READY) gnuplot of cross validation to not specifying -q random seed set portion (in [0.0:1.0]) from .AP files (atom pairs; will offset feat. indexes by 1) set (overrides -p) set (overrides -p) set (overrides -p) mode; use trained models mode; save trained models overwriting existing model file for best C scan #steps for SVR for best gamma ; also, implied by -e and --scan-e range for e (semantic=start:nsteps:stop) [--c-range <float,float,...>] explicit scan range for C (example='0.01,0.02,0.03') [--g-range <float,float,...>] explicit range for gamma (example='0.01,0.02,0.03') number of bags [--k-range <int,int,...>] explicit scan range for k (example='1,2,3,5,10') value for k [--r-range <float,float,...>] explicit range for r (example='0.01,0.02,0.03')