diff options
| -rw-r--r-- | CMakeLists.txt | 1 | ||||
| -rw-r--r-- | README | 24 | ||||
| -rw-r--r-- | model/rankaccu.cpp | 3 | ||||
| -rw-r--r-- | model/ranksvm.h | 2 | ||||
| -rw-r--r-- | split.cpp | 10 | ||||
| -rw-r--r-- | tools/dataProvider.h | 23 | ||||
| -rw-r--r-- | tools/fileDataProvider.cpp | 1 | ||||
| -rw-r--r-- | tools/fileDataProvider.h | 6 | ||||
| -rw-r--r-- | tools/matrixIO.h | 2 | ||||
| -rw-r--r-- | train.cpp | 23 |
10 files changed, 76 insertions, 19 deletions
diff --git a/CMakeLists.txt b/CMakeLists.txt index 97d548e..82aa7f4 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -14,6 +14,5 @@ INCLUDE_DIRECTORIES( ${Boost_INCLUDE_DIR}) set(SOURCE_FILES model/ranksvm.cpp model/ranksvmtn.cpp model/rankaccu.cpp tools/fileDataProvider.cpp) add_executable(ranksvm train.cpp ${SOURCE_FILES} model/rankaccu.h model/ranksvm.h model/ranksvmtn.h tools/dataProvider.h tools/matrixIO.h tools/fileDataProvider.h tools/dataProvider.cpp model/rankmisc.h) add_executable(split split.cpp ${SOURCE_FILES} tools/dataProvider.cpp) -add_dependencies(ranksvm split) TARGET_LINK_LIBRARIES( ranksvm ${Boost_LIBRARIES} ) TARGET_LINK_LIBRARIES( split ${Boost_LIBRARIES})
\ No newline at end of file @@ -0,0 +1,24 @@ +RankSVM Training, validating, & predicting +========================================== + +Acknowledgement: +Logging is provided by easylogging++ +up-to-date site: https://github.com/easylogging/easyloggingpp + +Requirements: +CMAKE, +GCC(C++) or any c++11 compatible compiler, +boost libraries(program_options), +Eigen3. + +How to build(Release): +1.copy the source files to an empty directory +2.mkdir Release +3.cd Release +# In the Release directory +4.cmake -DCMAKE_BUILD_TYPE=Release .. +# Change the Release to Debug for Debug build + +How to build it under windows(un-tested) +1.Install & configure: Eigen3 & boost +2.use cmake or VS
\ No newline at end of file diff --git a/model/rankaccu.cpp b/model/rankaccu.cpp index 0f55e26..caa3c5a 100644 --- a/model/rankaccu.cpp +++ b/model/rankaccu.cpp @@ -102,6 +102,7 @@ void rank_accu(RidList &D,const vector<double> pred) AP += ((double)C[k])/(k-j); AP=AP*2/(i-j)-1; accu_AP+=AP; + LOG(INFO)<<"qid:"<<D.getQid(j)<<"; nDCG:"<<Y/Z<<"; AP:"<< AP; } LOG(INFO)<<"over "<< D.getuSize()<< " queries. "<<"Average nDGC: "<< accu_nDCG/D.getuSize()<< " Average AP: "<<accu_AP/D.getuSize(); } @@ -127,6 +128,8 @@ void rank_CMC(RidList &D,const std::vector<double> pred,CMC & cmc) { cmc.addEntry(k-j); break; // account only for the first match; } + LOG(INFO)<<"top: "<< D.getO(pred_rank[j]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+1]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+2]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+3]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+4]%D.getqSize())->qid + <<" "<< D.getO(pred_rank[j+5]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+6]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+7]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+8]%D.getqSize())->qid <<" "<<D.getO(pred_rank[j+9]%D.getqSize())->qid; } } diff --git a/model/ranksvm.h b/model/ranksvm.h index a17e3c9..a19ad63 100644 --- a/model/ranksvm.h +++ b/model/ranksvm.h @@ -27,8 +27,6 @@ protected: public: virtual int train(RidList &D)=0; virtual int predict(RidList &D,std::vector<double> &res)=0; - // TODO Not sure how to construct this - // Possible solution: generate a nxn matrix each row contains the sorted list of ranker result. int saveModel(const std::string fname); static RSVM* loadModel(const std::string fname); virtual std::string getName()=0; @@ -1,6 +1,10 @@ -// -// Created by joe on 5/13/15. -// +/* + * split: helper program to split rid file + * usage: ./split -h to see all options + * support: + * shuffling + * splitting + */ #include <iostream> #include <boost/program_options.hpp> diff --git a/tools/dataProvider.h b/tools/dataProvider.h index eed3079..891be86 100644 --- a/tools/dataProvider.h +++ b/tools/dataProvider.h @@ -6,15 +6,12 @@ #include<vector> #include<math.h> -// TODO decide how to construct training data -// One possible way for training data: -// Matrix composed of an array of feature vectors -// Labels are composed of linked list, such as -// 6,3,4,0,5,0,0 -// => 0->6 | 1->3 | 2->4->5 -// How to compensate for non exhaustive labeling? -// Use -1 to indicate not yet labeled data -// -1s will be excluded from training +// Training data(Rid): +// First line: the total number of features(fsize) +// from the second line to last-1 +// nametag(string) fsize number of features for nametag +// possible: "-1" nametag mean don't care(partially implemented, not sure) +// last line(delimiter to terminate data read): 0 typedef struct DataEntry{ std::string qid; @@ -70,7 +67,6 @@ public: all.clear(); } void setfSize(int fsize){n=fsize;} - inline int getfSize(){return n;} void addEntry(DataEntry* d){ int ext=false; all.push_back(d); @@ -92,6 +88,8 @@ public: d->rank=uniq.size()-1; } } + // A lot of getters + inline int getfSize(){return n;} inline DataEntry* getU(int x) { return uniq[x]; @@ -182,9 +180,11 @@ public: } return res; } + // master cal -> possible multiplexing inline double cal(Eigen::VectorXd *id,Eigen::VectorXd *oth,int i) { return fabs((*id)[i] - (*oth)[i]); } + // TODO getvec as VectorXd -> deprecating due to performance issues inline Eigen::VectorXd getVec(int x){ int a,b,q=getqSize(); a=x/q; @@ -207,6 +207,7 @@ public: res(i)=cal(id,oth,i); return res; }; + // w*Vec -> linear factor inline double getVecDot(int x,const Eigen::VectorXd &w) { int a,b,q=getqSize(); @@ -230,6 +231,7 @@ public: res += cal(id,oth,i)*w[i]; return res; } + // w*Vec -> linear factor inline void addVecw(int x,double w,Eigen::VectorXd &X) { int a,b,q=getqSize(); @@ -251,6 +253,7 @@ public: for (int i=0;i<n;++i) X[i] += cal(id,oth,i)*w; } + // get label of vector x inline double getL(int x){ int a,b,q=getqSize(); a=x/q; diff --git a/tools/fileDataProvider.cpp b/tools/fileDataProvider.cpp index 2b52dc7..a0cbf9a 100644 --- a/tools/fileDataProvider.cpp +++ b/tools/fileDataProvider.cpp @@ -8,6 +8,7 @@ using namespace std; +// Random generator mt19937 gen; int FileDP::getDataSet(DataList &out){ diff --git a/tools/fileDataProvider.h b/tools/fileDataProvider.h index 0ab1948..1c40d6e 100644 --- a/tools/fileDataProvider.h +++ b/tools/fileDataProvider.h @@ -1,3 +1,6 @@ +// File Data Provider +// Any kind of dataprovider that reads from file + #ifndef FDPROV_H #define FDPROV_H @@ -8,7 +11,7 @@ #include <fstream> // Rank qid features - +// Deprecated due to algorithm update class FileDP:public DataProvider { private: @@ -23,7 +26,6 @@ public: }; // label features - class RidFileDP:public DataProvider { private: diff --git a/tools/matrixIO.h b/tools/matrixIO.h index 88cd419..ea5f85f 100644 --- a/tools/matrixIO.h +++ b/tools/matrixIO.h @@ -1,3 +1,5 @@ +// Some helper to read&write matrices data + #ifndef MATIO_H #define MATIO_H @@ -1,3 +1,24 @@ +/* + * ranksvm: main program + * usage: ./ranksvm -h to see all options + * support: + * training + * validating + * predicting + * model: + * TN RankSVM(truncated newton, conjugate gradient, various opt) + * BH bhat-dist + * HE Hell-dist(but output chance instead?!) + * out features: + * cmc + * Cumulative Matching Characteristic + * avg + * Normalized avg rank + * predict + * image pair relevance value + */ + + #include <iostream> #include <Eigen/Dense> #include <boost/program_options.hpp> @@ -190,7 +211,7 @@ int main(int argc, char **argv) { else return 0; DataProvider* dp; if (vm["feature"].as<string>().find(".rid") == string::npos) - LOG(FATAL)<<"Format not supported"; + LOG(FATAL)<<"Format no longer supported"; else { RidFileDP* tmpdp = new RidFileDP(vm["feature"].as<string>()); |