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tqchen
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@ -109,17 +109,6 @@ namespace xgboost{
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namespace xgboost{
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namespace xgboost{
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namespace regrank{
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namespace regrank{
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inline IObjFunction* CreateObjFunction( const char *name ){
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inline IObjFunction* CreateObjFunction( const char *name ){
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<<<<<<< HEAD
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if( !strcmp("reg", name ) ) return new RegressionObj();
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if( !strcmp("rank:pairwise", name ) ) return new PairwiseRankObj();
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if( !strcmp("rank:softmax", name ) ) return new SoftmaxRankObj();
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if( !strcmp("softmax", name ) ) return new SoftmaxMultiClassObj();
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if (!strcmp("rank:map", name)) return new LambdaRankObj_MAP();
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if (!strcmp("rank:ndcg", name)) return new LambdaRankObj_NDCG();
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utils::Error("unknown objective function type");
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return NULL;
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}
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=======
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if( !strcmp("reg:linear", name ) ) return new RegressionObj( LossType::kLinearSquare );
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if( !strcmp("reg:linear", name ) ) return new RegressionObj( LossType::kLinearSquare );
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if( !strcmp("reg:logistic", name ) ) return new RegressionObj( LossType::kLogisticNeglik );
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if( !strcmp("reg:logistic", name ) ) return new RegressionObj( LossType::kLogisticNeglik );
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if( !strcmp("binary:logistic", name ) ) return new RegressionObj( LossType::kLogisticClassify );
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if( !strcmp("binary:logistic", name ) ) return new RegressionObj( LossType::kLogisticClassify );
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@ -130,7 +119,6 @@ namespace xgboost{
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utils::Error("unknown objective function type");
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utils::Error("unknown objective function type");
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return NULL;
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return NULL;
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}
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}
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>>>>>>> 9eabb5c7f912a326005aca53a76c2e53a1661842
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};
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};
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};
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};
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#endif
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#endif
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@ -330,153 +330,6 @@ namespace xgboost{
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virtual ~PairwiseRankObj(void){}
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virtual ~PairwiseRankObj(void){}
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virtual void GetLambdaWeight( const std::vector<ListEntry> &sorted_list, std::vector<LambdaPair> &pairs ){}
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virtual void GetLambdaWeight( const std::vector<ListEntry> &sorted_list, std::vector<LambdaPair> &pairs ){}
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};
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};
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class LambdaRankObj_NDCG : public LambdaRankObj{
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public:
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virtual ~LambdaRankObj_NDCG(void){}
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inline float CalcDCG( const std::vector<float> &labels ){
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double sumdcg = 0.0;
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for( size_t i = 0; i < labels.size(); i ++ ){
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const unsigned rel = labels[i];
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if( rel != 0 ){
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sumdcg += logf(2.0f) * ((1<<rel)-1) / logf( i + 2 );
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}
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}
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return static_cast<float>(sumdcg);
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}
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inline float GetIDCG(const std::vector<ListEntry> &sorted_list){
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std::vector<float> labels;
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for (size_t i = 0; i < sorted_list.size(); i++){
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labels.push_back(sorted_list[i].label);
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}
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std::sort(labels.begin(), labels.end(), std::greater<float>());
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return CalcDCG(labels);
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}
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/*
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* \brief Obtain the delta NDCG if trying to switch the positions of instances in index1 or index2
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* in sorted triples. Here DCG is calculated as sigma_i 2^rel_i/log(i + 1)
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* \param sorted_list the list containing entry information
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* \param index1,index2 the instances switched
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* \param the IDCG of the list
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*/
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inline float GetLambdaNDCG(const std::vector<ListEntry> &sorted_list,
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int index1,
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int index2, float IDCG){
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double original = (1 << static_cast<int>(sorted_list[index1].label)) / log(index1 + 2)
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+ (1 << static_cast<int>(sorted_list[index2].label)) / log(index2 + 2);
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double changed = (1 << static_cast<int>(sorted_list[index2].label)) / log(index1 + 2)
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+ (1 << static_cast<int>(sorted_list[index1].label)) / log(index2 + 2);
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double ans = (original - changed) / IDCG;
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if (ans < 0) ans = -ans;
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return static_cast<float>(ans);
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}
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virtual void GetLambdaWeight(const std::vector<ListEntry> &sorted_list, std::vector<LambdaPair> &pairs){
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float IDCG = GetIDCG(sorted_list);
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for (size_t i = 0; i < pairs.size(); i++){
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pairs[i].weight = GetLambdaNDCG(sorted_list,
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pairs[i].pos_index, pairs[i].neg_index, IDCG);
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}
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}
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};
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class LambdaRankObj_MAP : public LambdaRankObj{
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class Quadruple{
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public:
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/* \brief the accumulated precision */
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float ap_acc_;
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/* \brief the accumulated precision assuming a positive instance is missing*/
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float ap_acc_miss_;
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/* \brief the accumulated precision assuming that one more positive instance is inserted ahead*/
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float ap_acc_add_;
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/* \brief the accumulated positive instance count */
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float hits_;
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Quadruple(){}
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Quadruple(const Quadruple& q){
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ap_acc_ = q.ap_acc_;
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ap_acc_miss_ = q.ap_acc_miss_;
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ap_acc_add_ = q.ap_acc_add_;
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hits_ = q.hits_;
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}
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Quadruple(float ap_acc, float ap_acc_miss, float ap_acc_add, float hits
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) :ap_acc_(ap_acc), ap_acc_miss_(ap_acc_miss), ap_acc_add_(ap_acc_add), hits_(hits){
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}
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};
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public:
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virtual ~LambdaRankObj_MAP(void){}
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/*
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* \brief Obtain the delta MAP if trying to switch the positions of instances in index1 or index2
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* in sorted triples
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* \param sorted_list the list containing entry information
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* \param index1,index2 the instances switched
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* \param map_acc a vector containing the accumulated precisions for each position in a list
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*/
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inline float GetLambdaMAP(const std::vector<ListEntry> &sorted_list,
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int index1, int index2,
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std::vector< Quadruple > &map_acc){
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if (index1 == index2 || sorted_list[index1].label == sorted_list[index2].label) return 0.0;
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if (index1 > index2) std::swap(index1, index2);
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float original = map_acc[index2].ap_acc_; // The accumulated precision in the interval [index1,index2]
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if (index1 != 0) original -= map_acc[index1 - 1].ap_acc_;
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float changed = 0;
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if (sorted_list[index1].label < sorted_list[index2].label){
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changed += map_acc[index2 - 1].ap_acc_add_ - map_acc[index1].ap_acc_add_;
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changed += (map_acc[index1].hits_ + 1.0f) / (index1 + 1);
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}
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else{
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changed += map_acc[index2 - 1].ap_acc_miss_ - map_acc[index1].ap_acc_miss_;
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changed += map_acc[index2].hits_ / (index2 + 1);
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}
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float ans = (changed - original) / (map_acc[map_acc.size() - 1].hits_);
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if (ans < 0) ans = -ans;
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return ans;
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}
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/*
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* \brief preprocessing results for calculating delta MAP
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* \return The first field is the accumulated precision, the second field is the
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* accumulated precision assuming a positive instance is missing,
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* the third field is the accumulated precision assuming that one more positive
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* instance is inserted, the fourth field is the accumulated positive instance count
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*/
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inline void GetMAPAcc(const std::vector<ListEntry> &sorted_list,
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std::vector< Quadruple > &map_acc){
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map_acc.resize(sorted_list.size());
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float hit = 0, acc1 = 0, acc2 = 0, acc3 = 0;
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for (size_t i = 1; i <= sorted_list.size(); i++){
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if ((int)sorted_list[i - 1].label == 1) {
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hit++;
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acc1 += hit / i;
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acc2 += (hit - 1) / i;
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acc3 += (hit + 1) / i;
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}
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map_acc[i - 1] = Quadruple(acc1, acc2, acc3, hit);
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}
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}
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virtual void GetLambdaWeight(const std::vector<ListEntry> &sorted_list, std::vector<LambdaPair> &pairs){
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std::vector< Quadruple > map_acc;
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GetMAPAcc(sorted_list, map_acc);
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for (size_t i = 0; i < pairs.size(); i++){
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pairs[i].weight = GetLambdaMAP(sorted_list, pairs[i].pos_index, pairs[i].neg_index, map_acc);
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}
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}
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};
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};
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};
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};
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};
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#endif
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#endif
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