thundergbm
ThunderGBM: Fast GBDTs and Random Forests on GPUs
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Download Latest Version (.zip)- machine.conf
- test_dataset.txt
- test_dataset.txt.group
- default.css
- lang-logo-tgbm.png
- overall.png
- tgbm-logo.png
- conf.py
- faq.md
- how-to.md
- index.md
- make.bat
- Makefile
- parameters.md
- README.md
- requirements.txt
- exact_tree_builder.h
- function_builder.h
- hist_tree_builder.h
- hist_tree_builder_single.h
- shard.h
- tree_builder.h
- metric.h
- multiclass_metric.h
- pointwise_metric.h
- ranking_metric.h
- multiclass_obj.h
- objective_function.h
- ranking_obj.h
- regression_obj.h
- cub_wrapper.h
- device_lambda.cuh
- log.h
- multi_device.h
- booster.h
- common.h
- config.h.in
- dataset.h
- hist_cut.h
- ins_stat.h
- parser.h
- predictor.h
- quantile_sketch.h
- row_sampler.h
- sparse_columns.h
- syncarray.h
- syncmem.h
- trainer.h
- tree.h
- __init__.py
- base_model.py
- catboost_model.py
- datasets.py
- lightgbm_model.py
- thundergbm_model.py
- xgboost_model.py
- __init__.py
- data_utils.py
- file_utils.py
- convert_dataset_plk.py
- experiments.py
- README.md
- run_exp.sh
- thundergbm-0.3.12-py2-none-win_amd64.whl
- thundergbm-0.3.12-py3-none-win_amd64.whl
- thundergbm-0.3.16-py3-none-any.whl
- thundergbm-0.3.4-py3-none-win_amd64.whl
- classification_demo.py
- ranking_demo.py
- regression_demo.py
- __init__.py
- thundergbm.py
- LICENSE
- README.md
- requirements.txt
- setup.py
- gbm.R
- README.md
- CMakeLists.txt
- googletest
- test_csr2csc.cpp
- test_cub_wrapper.cu
- test_dataset.cpp
- test_for_refactor.cpp
- test_gbdt.cpp
- test_get_cut_point.cpp
- test_gradient.cu
- test_main.cpp
- test_metrics.cpp
- test_parser.cpp
- test_synarray.cpp
- test_synmem.cpp
- test_tree.cpp
- exact_tree_builder.cu
- function_builder.cu
- hist_tree_builder.cu
- hist_tree_builder_single.cu
- shard.cu
- tree_builder.cu
- metric.cu
- multiclass_metric.cu
- pointwise_metric.cu
- rank_metric.cpp
- multiclass_obj.cu
- objective_function.cu
- ranking_obj.cpp
- common.cpp
- log.cpp
- CMakeLists.txt
- dataset.cpp
- gbm_R_interface.cpp
- hist_cut.cu
- parser.cpp
- predictor.cu
- quantile_sketch.cpp
- row_sampler.cu
- scikit_tgbm.cpp
- sparse_columns.cu
- syncmem.cpp
- thundergbm_predict.cpp
- thundergbm_train.cpp
- trainer.cu
- tree.cu
- .gitignore
- .gitmodules
- CMakeLists.txt
- cub
- LICENSE
- README.md
- thundergbm-full.pdf
# Installation Guide
1. Get the code
git clone https://github.com/Xtra-Computing/thundergbm
Downloads the entire project code from GitHub to your computer.
cd thundergbm
Moves into the project folder you just downloaded.
2. CMake
Medium RecommendedPrerequisites
mkdir build && cd build && cmake .. && make -j
Creates a folder to hold the build output and moves into it.
Check that an executable was created inside the build folder, then run it directly (e.g. ./build/app_name).
Pulled directly from this repo's README.
3. Python
EasyPrerequisites
* `pip install thundergbm`
Installs the Python libraries listed in requirements.txt (or similar).
* `pip install thundergbm-0.3.4-py3-none-win_amd64.whl`
Installs the Python libraries listed in requirements.txt (or similar).
If it runs without errors and prints output in the terminal, it worked.
Pulled directly from this repo's README.
// repository documentation
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