Docstring:
Usage: qiime feature-classifier fit-classifier-sklearn [OPTIONS]
Train a scikit-learn classifier to classify reads.
Inputs:
--i-reference-reads ARTIFACT FeatureData[Sequence]
[required]
--i-reference-taxonomy ARTIFACT FeatureData[Taxonomy]
[required]
--i-class-weight ARTIFACT FeatureTable[RelativeFrequency]
[optional]
Parameters:
--p-classifier-specification TEXT
[required]
Outputs:
--o-classifier ARTIFACT
TaxonomicClassifier [required]
Miscellaneous:
--output-dir PATH Output unspecified results to a directory
--verbose / --quiet Display verbose output to stdout and/or stderr
during execution of this action. Or silence output if
execution is successful (silence is golden).
--example-data PATH Write example data and exit.
--citations Show citations and exit.
--use-cache DIRECTORY Specify the cache to be used for the intermediate
work of this action. If not provided, the default
cache under $TMP/qiime2/ will be used.
IMPORTANT FOR HPC USERS: If you are on an HPC system
and are using parallel execution it is important to
set this to a location that is globally accessible to
all nodes in the cluster.
--help Show this message and exit.
Import:
from qiime2.plugins.feature_classifier.methods import fit_classifier_sklearn
Docstring:
Train an almost arbitrary scikit-learn classifier
Train a scikit-learn classifier to classify reads.
Parameters
----------
reference_reads : FeatureData[Sequence]
reference_taxonomy : FeatureData[Taxonomy]
classifier_specification : Str
class_weight : FeatureTable[RelativeFrequency], optional
Returns
-------
classifier : TaxonomicClassifier
