81 lines
2.9 KiB
C++
81 lines
2.9 KiB
C++
#ifndef XGBOOST_LEARNER_OBJECTIVE_H_
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#define XGBOOST_LEARNER_OBJECTIVE_H_
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/*!
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* \file objective.h
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* \brief interface of objective function used for gradient boosting
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* \author Tianqi Chen, Kailong Chen
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*/
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#include "dmatrix.h"
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namespace xgboost {
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namespace learner {
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/*! \brief interface of objective function */
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class IObjFunction{
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public:
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/*! \brief virtual destructor */
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virtual ~IObjFunction(void){}
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/*!
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* \brief set parameters from outside
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* \param name name of the parameter
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* \param val value of the parameter
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*/
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virtual void SetParam(const char *name, const char *val) = 0;
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/*!
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* \brief get gradient over each of predictions, given existing information
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* \param preds prediction of current round
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* \param info information about labels, weights, groups in rank
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* \param iter current iteration number
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* \param out_gpair output of get gradient, saves gradient and second order gradient in
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*/
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virtual void GetGradient(const std::vector<float>& preds,
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const MetaInfo &info,
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int iter,
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std::vector<bst_gpair> *out_gpair) = 0;
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/*! \return the default evaluation metric for the objective */
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virtual const char* DefaultEvalMetric(void) = 0;
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// the following functions are optional, most of time default implementation is good enough
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/*!
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* \brief transform prediction values, this is only called when Prediction is called
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* \param io_preds prediction values, saves to this vector as well
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*/
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virtual void PredTransform(std::vector<float> *io_preds){}
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/*!
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* \brief transform prediction values, this is only called when Eval is called,
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* usually it redirect to PredTransform
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* \param io_preds prediction values, saves to this vector as well
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*/
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virtual void EvalTransform(std::vector<float> *io_preds) {
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this->PredTransform(io_preds);
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}
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/*!
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* \brief transform probability value back to margin
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* this is used to transform user-set base_score back to margin
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* used by gradient boosting
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* \return transformed value
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*/
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virtual float ProbToMargin(float base_score) {
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return base_score;
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}
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};
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} // namespace learner
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} // namespace xgboost
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// this are implementations of objective functions
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#include "objective-inl.hpp"
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// factory function
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namespace xgboost {
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namespace learner {
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/*! \brief factory funciton to create objective function by name */
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inline IObjFunction* CreateObjFunction(const char *name) {
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if (!strcmp("reg:linear", name)) return new RegLossObj( LossType::kLinearSquare );
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if (!strcmp("reg:logistic", name)) return new RegLossObj( LossType::kLogisticNeglik );
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if (!strcmp("binary:logistic", name)) return new RegLossObj( LossType::kLogisticClassify );
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if (!strcmp("binary:logitraw", name)) return new RegLossObj( LossType::kLogisticRaw );
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utils::Error("unknown objective function type: %s", name);
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return NULL;
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}
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} // namespace learner
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} // namespace xgboost
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#endif // XGBOOST_LEARNER_OBJECTIVE_H_
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