Plugin error from feature-classifier

Hello QIIME2 communit,

As I am new and still learning bioinformatic and QIIME2 , 2019.1 in particular, using Virtualbox, I ran into this problem:
qiime feature-classifier classify-sklearn \

--i-classifier gg-13-8-99-nb-classifier.qza
--i-reads rep-seqs.qza
--o-classification taxonomy.qza

Plugin error from feature-classifier:

Debug info has been saved to /tmp/qiime2-q2cli-err-l9b_6vro.log

and when I run this command
less /tmp/qiime2-q2cli-err-l9b_6vro.log
this happend:
...
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/sklearn/pipeline.py", line 382, in predict_proba
return self.steps[-1][-1].predict_proba(Xt)
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/sklearn/naive_bayes.py", line 104, in predict_proba
return np.exp(self.predict_log_proba(X))
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/sklearn/naive_bayes.py", line 84, in predict_log_proba
jll = self._joint_log_likelihood(X)
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/sklearn/naive_bayes.py", line 731, in joint_log_likelihood
return (safe_sparse_dot(X, self.feature_log_prob
.T) +
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/sklearn/utils/extmath.py", line 168, in safe_sparse_dot
ret = a * b
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/scipy/sparse/base.py", line 473, in mul
return self._mul_multivector(other)
File "/home/qiime2/miniconda/envs/qiime2-2019.1/lib/python3.6/site-packages/scipy/sparse/compressed.py", line 482, in _mul_multivector
other.ravel(), result.ravel())
MemoryError

I tried to Train feature classifiers with q2-feature-classifier
this one was successful but did not fix the issue

I hope you can help..

Hi @hitham_Almughram,
See the line at the bottom of the error:

This is a memory error, and is a common problem with this method. Use the search bar to read how to troubleshoot this problem:
https://forum.qiime2.org/search?q=feature%20classifier%20memory%20error

hint: try a different classifier (e.g., greengenes) or use the reads-per-batch parameter.

Good luck!

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