Comments (5)
Fair enough. If you import the library, you can check the version with:
import tpot
print(tpot.__version__)
Should be easy enough to add --version as a command line parameter.
BTW: the export()
functionality has not been included with a release yet; it's only available in the dev version.
from tpot.
re: export() - thanks for clarifying - you may want to add a corresponding note to the example on the website, because that is kinda unexpected, i.e. most people will probably try to run your examples first
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I'll push out a new version to pip today with the export feature.
from tpot.
TPOT v0.2.0 is out on pip with the export functionality. Enjoy, and thanks for your feedback!
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once again, thank you for being so responsive!
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Related Issues (20)
- Question : Can multiple models be saved /exported from one Tpot optimization HOT 1
- Question: can we save all the evaluated pipelines as fitted model? HOT 1
- Questionable Score Fitting HOT 5
- Potential New Feature: allowing users to input customized initial pipelines HOT 1
- TPOT2 and the future of TPOT development -- From the Devs
- How can I be part of the project to develop new modules? HOT 2
- Documentation should use est=TPOTClassifier rather than tpot=TPOTClassifier
- Question: How is the data split using cross validation HOT 2
- In python 3.12, Get error after importing module. HOT 1
- How to map the features at the end of the pipeline back to the initial features HOT 1
- Can't import TPOTClassifier from tpot
- How long is the installation supposed to take HOT 3
- TPOTClassifier error for large data HOT 1
- TPOT error for xgboost multiclass classificaion HOT 1
- Unable to install pip ARM64 Mac HOT 5
- TPOT NN example fails
- last update of code and report HOT 1
- TPOT report error HOT 4
- Feature to Export the Pipeline/Model as pickle file HOT 1
- TPOT underpopulates a class, but manual sklearn does not HOT 4
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