training parameter for regression More...
Inheritance diagram for xgboost::LearnerModelParamLegacy:
Public Member Functions | |
| LearnerModelParamLegacy () | |
| constructor | |
| Json | ToJson () const |
| void | FromJson (Json const &obj) |
| LearnerModelParamLegacy | ByteSwap () const |
| template<typename Container > | |
| Args | UpdateAllowUnknown (Container const &kwargs) |
| void | Validate () |
| DMLC_DECLARE_PARAMETER (LearnerModelParamLegacy) | |
Data Fields | |
| bst_float | base_score |
| bst_feature_t | num_feature |
| std::int32_t | num_class |
| int32_t | contain_extra_attrs |
| Model contain additional properties. | |
| int32_t | contain_eval_metrics |
| Model contain eval metrics. | |
| std::uint32_t | major_version |
| the version of XGBoost. | |
| std::uint32_t | minor_version |
| bst_target_t | num_target |
| Number of target variables. | |
| std::int32_t | boost_from_average {true} |
| Whether we should calculate the base score from training data. | |
| int | reserved [25] |
| reserved field | |
Detailed Description
training parameter for regression
Should be deprecated, but still used for being compatible with binary IO. Once it's gone, LearnerModelParam should handle transforming base_margin with objective by itself.
Field Documentation
◆ boost_from_average
| std::int32_t xgboost::LearnerModelParamLegacy::boost_from_average {true} |
Whether we should calculate the base score from training data.
This is a private parameter as we can't expose it as boolean due to binary model format. Exposing it as integer creates inconsistency with other parameters.
Automatically disabled when base_score is specifed by user. int32 is used instead of bool for the ease of serialization.
The documentation for this struct was generated from the following file:
- External/xgboost/src/learner.cc
