blues
March 10, 2021, 11:51am
1
Hello good morning, I am trying to use the qiime feature-classifier classify-sklearn classifier with
What features would I need to have on my computer? How much memory is needed?
How can I solve this?
Thank you very much
jwdebelius
March 10, 2021, 4:18pm
2
Hi @blues ,
There's a lot of disucssion about this on the forum. Im not sure what your specific set up is, it may influence the right solution for you.
Best,
Dear all, I am trying feature-classifier for my taxonomic Analysis. When I executed this step, I got the error:
Plugin error from feature-classifier:
[Screenshot%20from%202018-05-08%2009-19-09]
My system configuration is:
Memory: 8 GB
Processor: Intel® Core™ i3-7100 CPU @ 3.90GHz × 4
Os: 64 bit
Am I getting these error due to my system configuration? Is there anyway I can solve this?
Dear all.
I am struggling for a while with a memory error from classifier. I trained it by myself using qiime2 2019.01. It worked fine with smaller dataset recently.
Here is the command I am using:
!qiime feature-classifier classify-sklearn \
--i-classifier training-feature-classifiers/classifier.qza \
--i-reads rep-seqs.qza \
--o-classification taxonomy.qza
And I am receiving an error:
Plugin error from feature-classifier:
Debug info has been saved to /home/bio/anaconda2/tempfiles/qi…
I am running the following command on qiime2-2019.4 (Linux terminal):
qiime feature-classifier fit-classifier-naive-bayes --i-reference-reads ref-seqs.qza --i-reference-taxonomy ref-taxonomy.qza --o-classifier SILVA_classifier99.qza --verbose
The process stops midway and I get the following message, suggesting a memory error. My ulimit parameters are appended at the end. The machine is quite powerful, any idea what's going on, and how to solve it?
/home/userx/miniconda3/envs/qiime2-2019…
I used MicrobiomeHelper for 16s V3-4 analysis. I had a problem in feature-classifier step as problem log show follows:
mh_user@MicrobiomeHelper:~ source activate qiime2-2018.6
(qiime2-2018.6) mh_user@MicrobiomeHelper:~ cd /media
(qiime2-2018.6) mh_user@MicrobiomeHelper:/media$ cd sf_shared_folder
(qiime2-2018.6) mh_user@MicrobiomeHelper:/media/sf_shared_folder$ cd working
(qiime2-2018.6) mh_user@MicrobiomeHelper:/media/sf_shared_folder/working$ qiime feature-classifier classify-sklearn --i-r…
Hi @ChristianEdwardson , I just re-read your post and realised that I was talking about training step (fit-classifier-naive-bayes) and you are talking about the classification step (classify-sklearn).
For the classification step, try leaving --p-n-jobs at its default value of 1. There is a trade-off here between memory usage and speed, so if you’re running out of memory you have to sacrifice speed to fit it in memory. The amount of memory you use should scale roughly linearly with the value of -…