diff --git a/README.md b/README.md index b35c0fe2..f0322ca9 100644 --- a/README.md +++ b/README.md @@ -25,7 +25,7 @@ The current version of TPOT was developed at Cedars-Sinai by: - Jay Moran (jay.moran@cshs.org) - Nicholas Matsumoto (nicholas.matsumoto@cshs.org) - Hyunjun Choi (hyunjun.choi@cshs.org) - - Gabriel Ketron (gabriel.ketron@cshs.org) + - Gabriel Ketron (gabriel.ketron@cshs.org) - Miguel E. Hernandez (miguel.e.hernandez@cshs.org) - Jason Moore (moorejh28@gmail.com) @@ -226,23 +226,36 @@ We welcome you to check the existing issues for bugs or enhancements to work on. If you use TPOT in a scientific publication, please consider citing at least one of the following papers: -Trang T. Le, Weixuan Fu and Jason H. Moore (2020). [Scaling tree-based automated machine learning to biomedical big data with a feature set selector](https://academic.oup.com/bioinformatics/article/36/1/250/5511404). *Bioinformatics*.36(1): 250-256. +Hernandez, J. G., Saini, A. K., Ghosh, A., & Moore, J. H. (2025). [The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning](https://www.cell.com/patterns/fulltext/S2666-3899(25)00162-X). Patterns, 6(7). BibTeX entry: -```bibtex -@article{le2020scaling, - title={Scaling tree-based automated machine learning to biomedical big data with a feature set selector}, - author={Le, Trang T and Fu, Weixuan and Moore, Jason H}, - journal={Bioinformatics}, - volume={36}, - number={1}, - pages={250--256}, - year={2020}, - publisher={Oxford University Press} +```bibtext +@article{hernandez2025tree, + title={The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning}, + author={Hernandez, Jose Guadalupe and Saini, Anil Kumar and Ghosh, Attri and Moore, Jason H}, + journal={Patterns}, + volume={6}, + number={7}, + year={2025}, + publisher={Elsevier} } ``` +Ribeiro, P., Saini, A., Moran, J., Matsumoto, N., Choi, H., Hernandez, M., & Moore, J. H. (2024). [TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning](https://link.springer.com/chapter/10.1007/978-981-99-8413-8_1). In Genetic programming theory and practice XX (pp. 1-17). Singapore: Springer Nature Singapore. + +BitTex entry: + +```bibtex +@incollection{ribeiro2024tpot2, + title={TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning}, + author={Ribeiro, Pedro and Saini, Anil and Moran, Jay and Matsumoto, Nicholas and Choi, Hyunjun and Hernandez, Miguel and Moore, Jason H}, + booktitle={Genetic programming theory and practice XX}, + pages={1--17}, + year={2024}, + publisher={Springer} +} +``` Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, and Jason H. Moore (2016). [Automating biomedical data science through tree-based pipeline optimization](http://link.springer.com/chapter/10.1007/978-3-319-31204-0_9). *Applications of Evolutionary Computation*, pages 123-137. @@ -286,6 +299,26 @@ BibTeX entry: } ``` +## Related Papers + +Trang T. Le, Weixuan Fu and Jason H. Moore (2020). [Scaling tree-based automated machine learning to biomedical big data with a feature set selector](https://academic.oup.com/bioinformatics/article/36/1/250/5511404). *Bioinformatics*.36(1): 250-256. + +BibTeX entry: + +```bibtex +@article{le2020scaling, + title={Scaling tree-based automated machine learning to biomedical big data with a feature set selector}, + author={Le, Trang T and Fu, Weixuan and Moore, Jason H}, + journal={Bioinformatics}, + volume={36}, + number={1}, + pages={250--256}, + year={2020}, + publisher={Oxford University Press} +} +``` + + ## Support for TPOT TPOT was developed in the [Artificial Intelligence Innovation (A2I) Lab](http://epistasis.org/) at Cedars-Sinai with funding from the [NIH](http://www.nih.gov/) under grants U01 AG066833 and R01 LM010098. We are incredibly grateful for the support of the NIH and the Cedars-Sinai during the development of this project. diff --git a/docs/cite.md b/docs/cite.md index ac7de6e6..5683a0ac 100644 --- a/docs/cite.md +++ b/docs/cite.md @@ -1,23 +1,36 @@ # Citing TPOT If you use TPOT in a scientific publication, please consider citing at least one of the following papers: -Trang T. Le, Weixuan Fu and Jason H. Moore (2020). [Scaling tree-based automated machine learning to biomedical big data with a feature set selector](https://academic.oup.com/bioinformatics/article/36/1/250/5511404). *Bioinformatics*.36(1): 250-256. +Hernandez, J. G., Saini, A. K., Ghosh, A., & Moore, J. H. (2025). [The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning](https://www.cell.com/patterns/fulltext/S2666-3899(25)00162-X). Patterns, 6(7). BibTeX entry: -```bibtex -@article{le2020scaling, - title={Scaling tree-based automated machine learning to biomedical big data with a feature set selector}, - author={Le, Trang T and Fu, Weixuan and Moore, Jason H}, - journal={Bioinformatics}, - volume={36}, - number={1}, - pages={250--256}, - year={2020}, - publisher={Oxford University Press} +```bibtext +@article{hernandez2025tree, + title={The tree-based pipeline optimization tool: Tackling biomedical research problems with genetic programming and automated machine learning}, + author={Hernandez, Jose Guadalupe and Saini, Anil Kumar and Ghosh, Attri and Moore, Jason H}, + journal={Patterns}, + volume={6}, + number={7}, + year={2025}, + publisher={Elsevier} } ``` +Ribeiro, P., Saini, A., Moran, J., Matsumoto, N., Choi, H., Hernandez, M., & Moore, J. H. (2024). [TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning](https://link.springer.com/chapter/10.1007/978-981-99-8413-8_1). In Genetic programming theory and practice XX (pp. 1-17). Singapore: Springer Nature Singapore. + +BitTex entry: + +```bibtex +@incollection{ribeiro2024tpot2, + title={TPOT2: A New Graph-Based Implementation of the Tree-Based Pipeline Optimization Tool for Automated Machine Learning}, + author={Ribeiro, Pedro and Saini, Anil and Moran, Jay and Matsumoto, Nicholas and Choi, Hyunjun and Hernandez, Miguel and Moore, Jason H}, + booktitle={Genetic programming theory and practice XX}, + pages={1--17}, + year={2024}, + publisher={Springer} +} +``` Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, and Jason H. Moore (2016). [Automating biomedical data science through tree-based pipeline optimization](http://link.springer.com/chapter/10.1007/978-3-319-31204-0_9). *Applications of Evolutionary Computation*, pages 123-137. @@ -59,4 +72,4 @@ BibTeX entry: publisher = {ACM}, address = {New York, NY, USA}, } -``` \ No newline at end of file +``` diff --git a/tpot/utils/eval_utils.py b/tpot/utils/eval_utils.py index 9b0a2ea3..1f5aa93b 100644 --- a/tpot/utils/eval_utils.py +++ b/tpot/utils/eval_utils.py @@ -33,6 +33,23 @@ License along with TPOT. If not, see . """ + +# pkg_resources.get_distribution() replacement for stopit compatibility +import importlib.util + +if importlib.util.find_spec("pkg_resources") is None: + from types import ModuleType + from importlib.metadata import version + import sys + fake_pkg_resources = ModuleType("pkg_resources") + setattr( + fake_pkg_resources, + "get_distribution", + lambda name: type("Distribution", (), {"version": version(name)})(), + ) + sys.modules["pkg_resources"] = fake_pkg_resources + + import types from abc import abstractmethod import numpy as np