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Hello, i have an error when i run the classifier step, i use the native qiime2-2020.2 version in a conda environment, my laptop GB RAM is bigger than 8.
What i run is:
$ qiime feature-classifier classify-sklearn --i-classifier classifier.qza --i-reads rep-seqs.qza --o-classification taxonomy.qza --verbose
And then i get:
Traceback (most recent call last):
File “/home/ubuntu/miniconda3/envs/qiime2-2020.2/lib/python3.6/site-packages/q2cli/commands.py”, line 328, in call
results = action(**arguments)
File “</home/ubuntu/miniconda3/envs/qiime2-2020.2/lib/python3.6/site-packages/decorator.py:decorator-gen-343>”, line 2, in classify_sklearn
File “/home/ubuntu/miniconda3/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/action.py”, line 234, in bound_callable
spec.view_type, recorder)
File “/home/ubuntu/miniconda3/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/sdk/result.py”, line 289, in _view
result = transformation(self._archiver.data_dir)
File “/home/ubuntu/miniconda3/envs/qiime2-2020.2/lib/python3.6/site-packages/qiime2/core/transform.py”, line 70, in transformation
new_view = transformer(view)
File “/home/ubuntu/miniconda3/envs/qiime2-2020.2/lib/python3.6/site-packages/q2_feature_classifier/_taxonomic_classifier.py”, line 64, in _1
% (sklearn_version, sklearn.version))
ValueError: The scikit-learn version (0.21.2) used to generate this artifact does not match the current version of scikit-learn installed (0.22.2.post1). Please retrain your classifier for your current deployment to prevent data-corruption errors.
Plugin error from feature-classifier:
The scikit-learn version (0.21.2) used to generate this artifact does not match the current version of scikit-learn installed (0.22.2.post1). Please retrain your classifier for your current deployment to prevent data-corruption errors.
See above for debug info.
So look for scikit-learn version (0.21.2) to install and I can’t to find it, now i think only exist the 0.22.2.post1 verrsion.
I really would apreciete your help. I dont know how to do in this issue. Thanks