diff options
| -rw-r--r-- | model/ranksvm.cpp | 6 | ||||
| -rw-r--r-- | model/ranksvm.h | 4 | ||||
| -rw-r--r-- | model/ranksvmtn.cpp | 6 | ||||
| -rw-r--r-- | train.cpp | 27 |
4 files changed, 26 insertions, 17 deletions
diff --git a/model/ranksvm.cpp b/model/ranksvm.cpp index 2f366d6..368e16d 100644 --- a/model/ranksvm.cpp +++ b/model/ranksvm.cpp @@ -15,11 +15,11 @@ int maxiter = 1; // max iteration count double prec=1e-10; // precision // conjugate gradient double cg_prec=1e-10; // precision -int cg_maxiter = 2000; +int cg_maxiter = 100; int ls_maxiter = 20; // line search -double line_prec=1e-10; // precision -double line_turb=1e-15; // purturbation +double ls_prec=1e-10; // precision +double ls_turb=1e-15; // purturbation int RSVM::saveModel(const string fname){ diff --git a/model/ranksvm.h b/model/ranksvm.h index 41de0f4..a17e3c9 100644 --- a/model/ranksvm.h +++ b/model/ranksvm.h @@ -46,7 +46,7 @@ extern double cg_prec; // precision extern int cg_maxiter; // not worth having a large number extern int ls_maxiter; // line search -extern double line_prec; // precision -extern double line_turb; // purturbation +extern double ls_prec; // precision +extern double ls_turb; // perturbation #endif
\ No newline at end of file diff --git a/model/ranksvmtn.cpp b/model/ranksvmtn.cpp index b599a03..4572484 100644 --- a/model/ranksvmtn.cpp +++ b/model/ranksvmtn.cpp @@ -192,12 +192,12 @@ int line_search(const VectorXd &w,RidList &D,const VectorXd &corr,const VectorXd g = grad.dot(step); cal_Hs(D,rank,corr,alpha,step,Hs); h = Hs.dot(step); - g=g+line_turb; - h = h+line_turb; + g=g+ls_turb; + h = h+ls_turb; t=t-g/h; ++iter; LOG(INFO) << "line search iter "<<iter<<", prec:"<<g*g/h; - if (g*g/h<line_prec) + if (g*g/h<ls_prec) break; if (iter >= ls_maxiter) { @@ -27,7 +27,9 @@ int train(DataProvider &dp) { LOG(INFO)<<"Training started"; dp.getAllDataSet(D); LOG(INFO)<<"Read "<<D.getSize()<<" entries with "<< D.getfSize()<<" features"; - LOG(INFO)<<"C: "<<C; + LOG(INFO)<<"C: "<<C<<" ,iter: "<<maxiter<<" ,prec: "<<prec; + LOG(INFO)<<"cg_maxiter: "<<cg_maxiter<<" ,cg_prec:"<<cg_prec<<" ,ls_maxiter: "<<ls_maxiter<<" ,ls_prec: "<<ls_prec; + rsvm->train(D); LOG(INFO)<<"Training finished,saving model"; @@ -109,7 +111,13 @@ int main(int argc, char **argv) { ("model,m", po::value<string>(), "set input model file") ("output,o", po::value<string>(), "set output model/prediction file") ("feature,i", po::value<string>(), "set input feature file") - ("c,c",po::value<double>(),"trades margin size against training error"); + ("c,c",po::value<double>(),"trades margin size against training error") + ("iter",po::value<int>(),"iter main") + ("prec",po::value<double>(),"prec main") + ("cg_iter",po::value<int>(),"iter conjugate gradient") + ("cg_prec",po::value<double>(),"prec conjugate gradient") + ("ls_iter",po::value<int>(),"iter line search") + ("ls_prec",po::value<double>(),"prec line search"); // Parsing program options po::store(po::parse_command_line(argc, argv, desc), vm); @@ -127,14 +135,15 @@ int main(int argc, char **argv) { el::Loggers::reconfigureLogger("default", defaultConf); mainFunc mainf; - if (vm.count("single")) - RidList::single=true; - else - RidList::single=false; + RidList::single=vm.count("single")>0; if (vm.count("train")) { - if (vm.count("c")) { - C=vm["c"].as<double>(); - } + if (vm.count("c")) { C=vm["c"].as<double>(); } + if (vm.count("iter")) { maxiter=vm["iter"].as<int>(); } + if (vm.count("prec")) { prec=vm["prec"].as<double>(); } + if (vm.count("cg_iter")) { cg_maxiter=vm["cg_iter"].as<int>(); } + if (vm.count("cg_prec")) { cg_prec=vm["cg_prec"].as<double>(); } + if (vm.count("ls_iter")) { ls_maxiter=vm["ls_iter"].as<int>(); } + if (vm.count("ls_prec")) { ls_prec=vm["ls_prec"].as<double>(); } mainf = &train; } else if (vm.count("validate")||vm.count("predict")) { |