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fit-classifier-sklearn: Train an almost arbitrary scikit-learn classifier

Citations
  • Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, and Édouard Duchesnay. Scikit-learn: machine learning in python. Journal of machine learning research, 12(Oct):2825–2830, 2011.

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.
  --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