Streaming Decision Trees & Forests: exploring streaming options for decision trees and random forests.
The package includes two ensemble implementations (Stream Decision Forest and Cascade Stream Forest).
Based on scikit-learn
fork.
You can manually download the latest version of SDTF
by cloning the repository:
git clone https://github.com/neurodata/SDTF cd SDTF python setup.py install
Or install the stable version through pip
:
pip install sdtf
The SDTF
package requires a scikit-learn
fork for the partial_fit
functionality,
which you can install manually:
git clone https://github.com/PSSF23/scikit-learn-stream cd scikit-learn-stream python setup.py install
The above local setup requires the following packages:
cython
numpy
scipy
- Very Fast Decision Tree
- Mondrian Forests
- Online Bagging and Boosting
- Leveraging Bagging for Evolving Data Streams
- Ensemble Learning for Data Stream Classification
- Adaptive Random Forests
- Streaming Random Forests
- Streaming Parallel Decision Tree
.. toctree:: :maxdepth: 1 iris select cc18 xor_experiments
.. toctree:: :maxdepth: 1 api