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