Classifier error during training

User Support
,
1

Hope you are well. I have an error during the training of the classifier:

qiime feature-classifier fit-classifier-naive-bayes --i-reference-reads ref_seqs.qza --i-reference-taxonomy silva132_99_ref_taxonomy.qza --o-classifier classifier.qza --verbose

/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_feature_classifier/classifier.py:101: UserWarning: The TaxonomicClassifier artifact that results from this method was trained using scikit-learn version 0.19.1. It cannot be used with other versions of scikit-learn. (While the classifier may complete successfully, the results will be unreliable.)
warnings.warn(warning, UserWarning)
Traceback (most recent call last):
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2cli/commands.py”, line 274, in call
results = action(**arguments)
File “”, line 2, in fit_classifier_naive_bayes
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/qiime2/sdk/action.py”, line 232, in bound_callable
output_types, provenance)
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/qiime2/sdk/action.py”, line 367, in callable_executor
output_views = self._callable(**view_args)
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_feature_classifier/classifier.py”, line 316, in generic_fitter
pipeline)
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_feature_classifier/_skl.py”, line 32, in fit_pipeline
pipeline.fit(X, y)
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/sklearn/pipeline.py”, line 250, in fit
self._final_estimator.fit(Xt, y, **fit_params)
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/q2_feature_classifier/custom.py”, line 41, in fit
classes=classes)
File “/home/qiime2/miniconda/envs/qiime2-2018.6/lib/python3.5/site-packages/sklearn/naive_bayes.py”, line 522, in partial_fit
dtype=np.float64)
MemoryError

Plugin error from feature-classifier:

See above for debug info.

Regards
Kianoosh

2

Hi @kia2094,
See the last line of that error message:

You are running out of memory. See this topic for tips to solve this.

Good luck!

3

Thank you for the reply Nicholas. Much appreciate it.

The link you sent me is asking to put the memory to 20GB memory. Isnt that a super computer? My mac has 8GB RAM.

Regards

4

No, that is high but many modern desktop computers have RAM within that range. A HPC cluster would easily cover this, and purchasing an AWS instance would too.

Alternatively, use the greengenes classifiers, which are smaller and less memory-intensive.

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5

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