Medial Code Documentation
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objective_function.h
1#ifndef LIGHTGBM_OBJECTIVE_FUNCTION_H_
2#define LIGHTGBM_OBJECTIVE_FUNCTION_H_
3
4#include <LightGBM/meta.h>
5#include <LightGBM/config.h>
6#include <LightGBM/dataset.h>
7#include <functional>
8
9namespace LightGBM {
14public:
16 virtual ~ObjectiveFunction() {}
17
23 virtual void Init(const Metadata& metadata, data_size_t num_data) = 0;
24
31 virtual void GetGradients(const double* score,
32 score_t* gradients, score_t* hessians) const = 0;
33
34 virtual const char* GetName() const = 0;
35
36 virtual bool IsConstantHessian() const { return false; }
37
38 virtual bool IsRenewTreeOutput() const { return false; }
39
40 virtual double RenewTreeOutput(double ori_output, const double*,
41 const data_size_t*,
42 const data_size_t*,
43 data_size_t) const { return ori_output; }
44
45 virtual double RenewTreeOutput(double ori_output, double,
46 const data_size_t*,
47 const data_size_t*,
48 data_size_t) const {
49 return ori_output;
50 }
51
52 virtual double BoostFromScore(int /*class_id*/) const { return 0.0; }
53
54 virtual bool ClassNeedTrain(int /*class_id*/) const { return true; }
55
56 virtual bool SkipEmptyClass() const { return false; }
57
58 virtual int NumModelPerIteration() const { return 1; }
59
60 virtual int NumPredictOneRow() const { return 1; }
61
63 virtual bool NeedAccuratePrediction() const { return true; }
64
65 virtual void ConvertOutput(const double* input, double* output) const {
66 output[0] = input[0];
67 }
68
69 virtual std::string ToString() const = 0;
70
71 ObjectiveFunction() = default;
76
82 LIGHTGBM_EXPORT static ObjectiveFunction* CreateObjectiveFunction(const std::string& type,
83 const Config& config);
84
88 LIGHTGBM_EXPORT static ObjectiveFunction* CreateObjectiveFunction(const std::string& str);
89};
90
91} // namespace LightGBM
92
93#endif // LightGBM_OBJECTIVE_FUNCTION_H_
This class is used to store some meta(non-feature) data for training data, e.g. labels,...
Definition dataset.h:36
The interface of Objective Function.
Definition objective_function.h:13
virtual bool NeedAccuratePrediction() const
The prediction should be accurate or not. True will disable early stopping for prediction.
Definition objective_function.h:63
ObjectiveFunction(const ObjectiveFunction &)=delete
Disable copy.
ObjectiveFunction & operator=(const ObjectiveFunction &)=delete
Disable copy.
virtual void GetGradients(const double *score, score_t *gradients, score_t *hessians) const =0
calculating first order derivative of loss function
static LIGHTGBM_EXPORT ObjectiveFunction * CreateObjectiveFunction(const std::string &type, const Config &config)
Create object of objective function.
Definition objective_function.cpp:10
virtual void Init(const Metadata &metadata, data_size_t num_data)=0
Initialize.
virtual ~ObjectiveFunction()
virtual destructor
Definition objective_function.h:16
desc and descl2 fields must be written in reStructuredText format
Definition application.h:10
float score_t
Type of score, and gradients.
Definition meta.h:26
int32_t data_size_t
Type of data size, it is better to use signed type.
Definition meta.h:14
Definition config.h:27