pygbm
Experimental Gradient Boosting Machines in Python with numba.
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Download Latest Version (.zip)- bench_binning.py
- bench_higgs_boson.py
- bench_histogram.py
- bench_predictor.py
- conf.py
- index.rst
- private_api.rst
- public_api.rst
- make.bat
- Makefile
- early_stopping.py
- grid_search.py
- plot_performance_profile_single_small_tree.py
- __init__.py
- binning.py
- gradient_boosting.py
- grower.py
- histogram.py
- loss.py
- multiclass_notes
- plotting.py
- predictor.py
- splitting.py
- utils.py
- test_binning.py
- test_compare_lightgbm.py
- test_gradient_boosting.py
- test_grower.py
- test_histogram.py
- test_loss.py
- test_plotting.py
- test_predictor.py
- test_splitting.py
- .gitignore
- .travis.yml
- CHANGELOG.md
- LICENSE.txt
- README.md
- readthedocs.yml
- requirements.txt
- ROADMAP.md
- setup.py
- tox.ini
# Installation Guide
git clone https://github.com/ogrisel/pygbm
Downloads the entire project code from GitHub to your computer.
cd pygbm
Moves into the project folder you just downloaded.
2. Official Install Script
Easy Recommended- Python 3 Python is required to use pip.
pip install pygbm
Installs the package published on PyPI directly โ no need to clone the source.
pip install --editable .
Installs the package published on PyPI directly โ no need to clone the source.
pip install snakeviz
Installs the package published on PyPI directly โ no need to clone the source.
Pulled directly from this repo's README.
3. Python
Easypip install pygbm
Installs the package published on PyPI directly โ no need to clone the source.
pip install -r requirements.txt
Installs the Python libraries listed in requirements.txt (or similar).
pip install --editable .
Installs the package published on PyPI directly โ no need to clone the source.
pip install snakeviz
Installs the package published on PyPI directly โ no need to clone the source.
python -m cProfile -o bench_higgs_boson.prof benchmarks/bench_higgs_boson.py
Runs the Python script (or module).
Pulled directly from this repo's README.
4. Make
Medium- Git Needed to download the project code from GitHub.
- Make Usually pre-installed on Linux/macOS. On Windows, install separately (e.g. via MSYS2 or WSL).
cd doc
This project's files live in a subfolder, so move into it first.
make
Compiles the code based on the generated build configuration to produce an executable.