merged mutating_versions into master

[milanflach]

Replaces #17
The version allocates memory for prediction already during training. In addition it provides a svmpredict! version by writing the output into a preallocated svmtmp type.
The gain in performance of the new svmpredict! can best be seen, when using large matrices, e.g. computing the kernel matrix for the svm model explicitly in julia:

Example

using LIBSVM
using Distances
train = randn(3,5000);
D = pairwise(Euclidean(), train);
K = exp(-0.5.*D); #transform to simple kernel matrix

test = randn(3, 300);
Dtest = pairwise(Euclidean(), train, test);
Ktest = exp(-0.5.*Dtest);

@time model = svmtrain(K, svmtype = OneClassSVM, nu = 0.1, kernel = Kernel.Precomputed);

0.5s 440 mb new; 0.4 s, 400 Mb old version

gc()
@time (class, decvalues) = svmpredict(model, Ktest)

22 mb 0.01 s new; 0.04 s, 61 mb old version

@time svmtmp = LIBSVM.init_svmpredict(Ktest, model) # 22mb, 0.005s

@time LIBSVM.svmpredict!(svmtmp, model, Ktest) # 20kb, 0.004 s --> about 10 time speedup

[coveralls]

Coverage increased (+0.1%) to 82.511% when pulling f90f907 on milanflach:mut_merge into 726d20d on mpastell:master.

[milanflach]

@mpastell did you have time to look into this version? Would be nice to merge it... Milan