# Sklearn-classifier bug for archaea 16s amplicons

**URL:** https://forum.qiime2.org/t/sklearn-classifier-bug-for-archaea-16s-amplicons/13397
**Category:** Technical Support
**Tags:** taxonomy
**Created:** [January 30, 2020, 1:07pm UTC](https://forum.qiime2.org/t/sklearn-classifier-bug-for-archaea-16s-amplicons/13397 "2020-01-30T13:07:01Z")
**Posts on this page:** 1
**Showing post:** 3

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### Author: ![Nicholas\_Bokulich](https://forum.qiime2.org/user_avatar/forum.qiime2.org/nicholas_bokulich/32/19937_2.png) [@Nicholas\_Bokulich](https://forum.qiime2.org/u/Nicholas_Bokulich)
#### Post date: [January 30, 2020, 11:24pm UTC](https://forum.qiime2.org/t/sklearn-classifier-bug-for-archaea-16s-amplicons/13397/3 "2020-01-30T23:24:30Z")

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Hi @mol,  
Just a couple things to add to @SoilRotifer's advice.

The sklearn classifier should not give different classifications each time you run it... _unless_ if your sequences are in mixed orientations, which confuses the classifier as described here:

> [@unassigned taxa - oddly reversed between deblur and dada2 pipeline \*so confused\*](https://forum.qiime2.org/t/unassigned-taxa-oddly-reversed-between-deblur-and-dada2-pipeline-so-confused/11696/11):
>
> classify-sklearn cannot currently handle reads in mixed orientations — it guesses the orientation of reads based on the first 100 or so, and then processes them accordingly, but if reads in the opposite orientation crop up it becomes discombobulated. Those samples for some reason must have their reads in opposing orientations. For your workshop I would recommend just excluding those samples, or use classify-consensus-vsearch to avoid this issue.

So that explains why removing one sequence causes the results to change, and also probably why a few of these classify as Archaea and the others as Bacteria.

Even though you are using extract-reads, you are probably hitting a few bacterial sequences. classify-sklearn would not give bacterial classifications unless if this annotation is present in the (trimmed) reference database that you are using.

So in addition to @SoilRotifer's advice about starting with the full-length database, I'd advise trying to orient your sequences in the same direction. Unfortunately QIIME 2 can't do that for you right now. Another option is to use `classify-consensus-vsearch`, which is able to handle mixed-orientation sequences.

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