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


[feature-classifier:fit-classifier-sklearn:PVG+11]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.


Usage: qiime feature-classifier fit-classifier-sklearn [OPTIONS]

  Train a scikit-learn classifier to classify reads.

  --i-reference-reads ARTIFACT PATH FeatureData[Sequence]
  --i-reference-taxonomy ARTIFACT PATH FeatureData[Taxonomy]
  --p-classifier-specification TEXT
  --i-class-weight ARTIFACT PATH FeatureTable[RelativeFrequency]
  --o-classifier ARTIFACT PATH TaxonomicClassifier
                                  [required if not passing --output-dir]
  --output-dir DIRECTORY          Output unspecified results to a directory
  --cmd-config FILE               Use config file for command options
  --verbose                       Display verbose output to stdout and/or
                                  stderr during execution of this action.
                                  [default: False]
  --quiet                         Silence output if execution is successful
                                  (silence is golden).  [default: False]
  --citations                     Show citations and exit.
  --help                          Show this message and exit.


from qiime2.plugins.feature_classifier.methods import fit_classifier_sklearn


Train an almost arbitrary scikit-learn classifier

Train a scikit-learn classifier to classify reads.

reference_reads : FeatureData[Sequence]
reference_taxonomy : FeatureData[Taxonomy]
classifier_specification : Str
class_weight : FeatureTable[RelativeFrequency], optional

classifier : TaxonomicClassifier