Comments (5)
from tpot.
I do not have a mac with the new processors, but I'll ask people on the team who do to test this out.
In the meantime you could try the next version of TPOT, TPOT2 which can be found here: https://github.com/EpistasisLab/tpot2
This version does not use the deap package and has been working for people on our team with newer Macs.
from tpot.
We were able to install this on a Mac with the new processor.
I would recommend trying to install Deap/tpot using conda rather than pip.
from tpot.
from tpot.
to install via conda, you need to include the conda-forge channel.
Here is the command:
conda install -c conda-forge tpot
from tpot.
Related Issues (20)
- 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
- 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
- macos
- Tpot affects the nb of jobs at import HOT 1
- How to use tpot with MLFlow HOT 5
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from tpot.