sdtf 0.0.9

Exploring streaming options for decision trees and random forests. Based on scikit-learn fork.

Streaming Decision Trees & Forests

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.. doc-start

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 <https://github.com/neurodata/scikit-learn/tree/stream>_.

Install

You can manually download the latest version of SDTF by cloning the repository:

.. code-block::

git clone https://github.com/neurodata/SDTF cd SDTF python setup.py install

Or install the stable version through pip\ :

.. code-block::

pip install sdtf

Package Requirements

The SDTF package requires a scikit-learn fork for the partial_fit functionality, which you can install manually:

.. code-block::

git clone https://github.com/neurodata/scikit-learn -b stream --single-branch cd scikit-learn python setup.py install

The above local setup requires the following packages:

• cython
• numpy
• scipy

.. doc-end

Relevant Repos

• huawei-noah/streamDM <https://github.com/huawei-noah/streamDM>_
• soundcloud/spdt <https://github.com/soundcloud/spdt>_
• online-ml/river <https://github.com/online-ml/river>_
• scikit-garden/scikit-garden <https://github.com/scikit-garden/scikit-garden>_

Relevant Papers

• Very Fast Decision Tree <https://dl.acm.org/doi/10.1145/347090.347107>_
• Online Bagging and Boosting <https://ieeexplore.ieee.org/document/1571498>_
• Leveraging Bagging for Evolving Data Streams <https://link.springer.com/chapter/10.1007/978-3-642-15880-3_15>_
• Ensemble Learning for Data Stream Classification <https://dl.acm.org/doi/10.1145/3054925>_
• Adaptive Random Forests <https://link.springer.com/article/10.1007/s10994-017-5642-8>_
• Streaming Random Forests <https://ieeexplore.ieee.org/document/4318108>_
• Streaming Parallel Decision Tree <https://www.jmlr.org/papers/v11/ben-haim10a.html>_
• Mondrian Forests <https://papers.nips.cc/paper/5234-mondrian-forests-efficient-online-random-forests.pdf>_