Hi all,
I am now experiencing some errors while trying to use the following:
qiime feature-classifier classify-sklearn
the error I get is the following:
ValueError: The scikit-learn version (0.21.2) used to generate this artifact does not match the current version of scikit-learn installed (0.24.1). Please retrain your classifier for your current deployment to prevent data-corruption errors
I have found the following guidelines from your documentation regarding feature classifier:
https://docs.qiime2.org/2021.11/tutorials/feature-classifier/
however I would need the fasta sequences and OTU assignments
where could I find those files?
using the following file:
Greengenes 13_8 99% OTUs full-length sequences (
the problem persists, so I was wondering if I could regenerate from fasta sequences and taxonomy as indicated in the tutoriale page, however I would need 99% instead of 85% identity
I report version details
qiime infoSystem versions
Python version: 3.8.10
QIIME 2 release: 2021.8
QIIME 2 version: 2021.8.0
q2cli version: 2021.8.0
Installed plugins
alignment: 2021.8.0
composition: 2021.8.0
cutadapt: 2021.8.0
dada2: 2021.8.0
deblur: 2021.8.0
demux: 2021.8.0
diversity: 2021.8.0
diversity-lib: 2021.8.0
emperor: 2021.8.0
feature-classifier: 2021.8.0
feature-table: 2021.8.0
fragment-insertion: 2021.8.0
gneiss: 2021.8.0
longitudinal: 2021.8.0
metadata: 2021.8.0
phylogeny: 2021.8.0
quality-control: 2021.8.0
quality-filter: 2021.8.0
sample-classifier: 2021.8.0
taxa: 2021.8.0
types: 2021.8.0
vsearch: 2021.8.0
thanks a lot,
I have read that it is possible to use classifiers already available, referred to the specific qiime version, I used the appropriate file in the appropriate version, available here:
https://docs.qiime2.org/2021.8/data-resources/
and solved the issue
Michela