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Implement weighted bootstrap sampling for RF #8296

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Merged
rapids-bot merged 10 commits into from
Jul 1, 2026
Merged

Implement weighted bootstrap sampling for RF #8296

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1c31701
Implement weighted bootstrap sampling for RF
RAMitchell Jun 26, 2026
836fbbc
Restore RF bootstrap masks in row sampler
RAMitchell Jun 26, 2026
fe8a3e0
Restore mask-based RF bootstrap tests
RAMitchell Jun 26, 2026
c0cc2cd
Harden RF bootstrap mask writes
RAMitchell Jun 26, 2026
e1883ec
Address RF row sampler review comments
RAMitchell Jun 29, 2026
37ca3af
Merge remote-tracking branch 'upstream/main' into codex/enh-rf-weight…
RAMitchell Jun 29, 2026
29570e0
Merge branch 'main' into codex/enh-rf-weighted-bootstrap
RAMitchell Jun 29, 2026
3ce70db
Merge branch 'main' into codex/enh-rf-weighted-bootstrap
RAMitchell Jun 30, 2026
6841286
Merge branch 'main' into codex/enh-rf-weighted-bootstrap
RAMitchell Jul 1, 2026
0ab1b4d
Merge branch 'main' into codex/enh-rf-weighted-bootstrap
RAMitchell Jul 1, 2026
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8 changes: 4 additions & 4 deletions cpp/include/cuml/ensemble/randomforest.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@ void fit(const raft::handle_t& user_handle,
RF_params rf_params,
rapids_logger::level_enum verbosity = rapids_logger::level_enum::info,
bool* bootstrap_masks = nullptr,
const float* sample_weight = nullptr);
const double* sample_weight = nullptr);
void fit(const raft::handle_t& user_handle,
RandomForestClassifierD* forest,
double* input,
Expand All @@ -177,7 +177,7 @@ void fit_treelite(const raft::handle_t& user_handle,
bool* bootstrap_masks,
T* feature_importances,
rapids_logger::level_enum verbosity,
const T* sample_weight = nullptr);
const double* sample_weight = nullptr);

void predict(const raft::handle_t& user_handle,
const RandomForestClassifierF* forest,
Expand Down Expand Up @@ -236,7 +236,7 @@ void fit(const raft::handle_t& user_handle,
RF_params rf_params,
rapids_logger::level_enum verbosity = rapids_logger::level_enum::info,
bool* bootstrap_masks = nullptr,
const float* sample_weight = nullptr);
const double* sample_weight = nullptr);
void fit(const raft::handle_t& user_handle,
RandomForestRegressorD* forest,
double* input,
Expand All @@ -259,7 +259,7 @@ void fit_treelite(const raft::handle_t& user_handle,
bool* bootstrap_masks,
T* feature_importances,
rapids_logger::level_enum verbosity,
const T* sample_weight = nullptr);
const double* sample_weight = nullptr);

void predict(const raft::handle_t& user_handle,
const RandomForestRegressorF* forest,
Expand Down
2 changes: 1 addition & 1 deletion cpp/src/decisiontree/batched-levelalgo/builder.cuh
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Expand Up @@ -202,7 +202,7 @@ struct Builder {
const DecisionTreeParams& p,
const DataT* data,
const LabelT* labels,
const DataT* sample_weight,
const double* sample_weight,
IdxT n_rows,
IdxT n_cols,
rmm::device_uvector<IdxT>* row_ids,
Expand Down
2 changes: 1 addition & 1 deletion cpp/src/decisiontree/batched-levelalgo/dataset.h
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Expand Up @@ -15,7 +15,7 @@ struct Dataset {
/** input labels */
const LabelT* labels;
/** optional input sample weights */
const DataT* sample_weight;
const double* sample_weight;
/** total rows in dataset */
IdxT M;
/** total cols in dataset */
Expand Down
2 changes: 1 addition & 1 deletion cpp/src/decisiontree/decisiontree.cuh
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Expand Up @@ -244,7 +244,7 @@ class DecisionTree {
uint64_t seed,
const Quantiles<DataT, int>& quantiles,
int treeid,
const DataT* sample_weight = nullptr)
const double* sample_weight = nullptr)
{
if (params.split_criterion ==
CRITERION::CRITERION_END) { // Set default to GINI (classification) or MSE (regression)
Expand Down
12 changes: 6 additions & 6 deletions cpp/src/randomforest/randomforest.cu
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Expand Up @@ -358,7 +358,7 @@ void fit(const raft::handle_t& user_handle,
RF_params rf_params,
rapids_logger::level_enum verbosity,
bool* bootstrap_masks,
const float* sample_weight)
const double* sample_weight)
{
raft::common::nvtx::range fun_scope("RF::fit @randomforest.cu");
ML::default_logger().set_level(verbosity);
Expand Down Expand Up @@ -422,7 +422,7 @@ void fit_treelite(const raft::handle_t& user_handle,
bool* bootstrap_masks,
value_t* feature_importances,
rapids_logger::level_enum verbosity,
const value_t* sample_weight)
const double* sample_weight)
{
RandomForestMetaData<value_t, label_t> metadata;
fit(user_handle,
Expand Down Expand Up @@ -605,7 +605,7 @@ void fit(const raft::handle_t& user_handle,
RF_params rf_params,
rapids_logger::level_enum verbosity,
bool* bootstrap_masks,
const float* sample_weight)
const double* sample_weight)
{
raft::common::nvtx::range fun_scope("RF::fit @randomforest.cu");
ML::default_logger().set_level(verbosity);
Expand Down Expand Up @@ -653,7 +653,7 @@ void fit_treelite(const raft::handle_t& user_handle,
bool* bootstrap_masks,
value_t* feature_importances,
rapids_logger::level_enum verbosity,
const value_t* sample_weight)
const double* sample_weight)
{
RandomForestMetaData<value_t, label_t> metadata;
fit(user_handle,
Expand Down Expand Up @@ -873,7 +873,7 @@ template CUML_EXPORT void fit_treelite<float, int>(const raft::handle_t& user_ha
bool* bootstrap_masks,
float* feature_importances,
rapids_logger::level_enum verbosity,
const float* sample_weight);
const double* sample_weight);
template CUML_EXPORT void fit_treelite<double, int>(const raft::handle_t& user_handle,
TreeliteModelHandle* model,
double* input,
Expand All @@ -896,7 +896,7 @@ template CUML_EXPORT void fit_treelite<float, float>(const raft::handle_t& user_
bool* bootstrap_masks,
float* feature_importances,
rapids_logger::level_enum verbosity,
const float* sample_weight);
const double* sample_weight);
template CUML_EXPORT void fit_treelite<double, double>(const raft::handle_t& user_handle,
TreeliteModelHandle* model,
double* input,
Expand Down
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