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xgboost/include/xgboost/gbm.h  view on Meta::CPAN

   * \param ntree_limit limit the number of trees used in prediction, when it equals 0, this means
   *    we do not limit number of trees, this parameter is only valid for gbtree, but not for gblinear
   */
  virtual void PredictLeaf(DMatrix* dmat,
                           std::vector<bst_float>* out_preds,
                           unsigned ntree_limit = 0) = 0;

  /*!
   * \brief feature contributions to individual predictions; the output will be a vector
   *         of length (nfeats + 1) * num_output_group * nsample, arranged in that order
   * \param dmat feature matrix
   * \param out_contribs output vector to hold the contributions
   * \param ntree_limit limit the number of trees used in prediction, when it equals 0, this means
   *    we do not limit number of trees
   */
  virtual void PredictContribution(DMatrix* dmat,
                           std::vector<bst_float>* out_contribs,
                           unsigned ntree_limit = 0) = 0;

  /*!
   * \brief dump the model in the requested format
   * \param fmap feature map that may help give interpretations of feature
   * \param with_stats extra statistics while dumping model
   * \param format the format to dump the model in
   * \return a vector of dump for boosters.
   */
  virtual std::vector<std::string> DumpModel(const FeatureMap& fmap,
                                             bool with_stats,
                                             std::string format) const = 0;
  /*!
   * \brief create a gradient booster from given name
   * \param name name of gradient booster
   * \param cache_mats The cache data matrix of the Booster.
   * \param base_margin The base margin of prediction.
   * \return The created booster.
   */
  static GradientBooster* Create(
      const std::string& name,
      const std::vector<std::shared_ptr<DMatrix> >& cache_mats,
      bst_float base_margin);
};

// implementing configure.
template<typename PairIter>
inline void GradientBooster::Configure(PairIter begin, PairIter end) {
  std::vector<std::pair<std::string, std::string> > vec(begin, end);
  this->Configure(vec);
}

/*!
 * \brief Registry entry for tree updater.
 */
struct GradientBoosterReg
    : public dmlc::FunctionRegEntryBase<
  GradientBoosterReg,
  std::function<GradientBooster* (const std::vector<std::shared_ptr<DMatrix> > &cached_mats,
                                  bst_float base_margin)> > {
};

/*!
 * \brief Macro to register gradient booster.
 *
 * \code
 * // example of registering a objective ndcg@k
 * XGBOOST_REGISTER_GBM(GBTree, "gbtree")
 * .describe("Boosting tree ensembles.")
 * .set_body([]() {
 *     return new GradientBooster<TStats>();
 *   });
 * \endcode
 */
#define XGBOOST_REGISTER_GBM(UniqueId, Name)                            \
  static DMLC_ATTRIBUTE_UNUSED ::xgboost::GradientBoosterReg &          \
  __make_ ## GradientBoosterReg ## _ ## UniqueId ## __ =                \
      ::dmlc::Registry< ::xgboost::GradientBoosterReg>::Get()->__REGISTER__(Name)

}  // namespace xgboost
#endif  // XGBOOST_GBM_H_