MR_LIBS/fit__stump_8h_source.html

#ifndef XGBOOST_TREE_FIT_STUMP_H_

#define XGBOOST_TREE_FIT_STUMP_H_


#if !defined(NOMINMAX) && defined(_WIN32)

#define NOMINMAX

#endif  // !defined(NOMINMAX)


#include <algorithm>  // std::max


#include "../common/common.h"            // AssertGPUSupport

#include "xgboost/base.h"                // GradientPair

#include "xgboost/context.h"             // Context

#include "xgboost/data.h"                // MetaInfo

#include "xgboost/host_device_vector.h"  // HostDeviceVector

#include "xgboost/linalg.h"              // TensorView


namespace xgboost {

namespace tree {


template <typename T>

XGBOOST_DEVICE inline double CalcUnregularizedWeight(T sum_grad, T sum_hess) {

  return -sum_grad / std::max(sum_hess, static_cast<double>(kRtEps));

}


void FitStump(Context const* ctx, MetaInfo const& info, HostDeviceVector<GradientPair> const& gpair,

              bst_target_t n_targets, linalg::Vector<float>* out);

}  // namespace tree

}  // namespace xgboost

#endif  // XGBOOST_TREE_FIT_STUMP_H_

context.h
Copyright 2014-2023, XGBoost Contributors.

host_device_vector.h
A device-and-host vector abstraction layer.

base.h
Copyright 2015-2023 by XGBoost Contributors.

XGBOOST_DEVICE
#define XGBOOST_DEVICE
Tag function as usable by device.
Definition base.h:64

data.h
Copyright 2015-2023 by XGBoost Contributors.

linalg.h
Copyright 2021-2023 by XGBoost Contributors.

xgboost::tree::FitStump
void FitStump(Context const *ctx, MetaInfo const &info, HostDeviceVector< GradientPair > const &gpair, bst_target_t n_targets, linalg::Vector< float > *out)
Fit a tree stump as an estimation of base_score.
Definition fit_stump.cc:69

xgboost
namespace of xgboost
Definition base.h:90

xgboost::bst_target_t
std::uint32_t bst_target_t
Type for indexing into output targets.
Definition base.h:118

xgboost::kRtEps
constexpr bst_float kRtEps
small eps gap for minimum split decision.
Definition base.h:319