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fit-classifier-naive-bayes: Train the naive_bayes classifier¶
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Docstring:
Usage: qiime feature-classifier fit-classifier-naive-bayes
[OPTIONS]
Create a scikit-learn naive_bayes classifier for 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-classify--alpha NUMBER
[default: 0.001]
--p-classify--chunk-size INTEGER
[default: 20000]
--p-classify--class-prior TEXT
[default: 'null']
--p-classify--fit-prior / --p-no-classify--fit-prior
[default: False]
--p-feat-ext--alternate-sign / --p-no-feat-ext--alternate-sign
[default: False]
--p-feat-ext--analyzer TEXT
[default: 'char_wb']
--p-feat-ext--binary / --p-no-feat-ext--binary
[default: False]
--p-feat-ext--decode-error TEXT
[default: 'strict']
--p-feat-ext--encoding TEXT
[default: 'utf-8']
--p-feat-ext--input TEXT
[default: 'content']
--p-feat-ext--lowercase / --p-no-feat-ext--lowercase
[default: True]
--p-feat-ext--n-features INTEGER
[default: 8192]
--p-feat-ext--ngram-range TEXT
[default: '[7, 7]']
--p-feat-ext--norm TEXT
[default: 'l2']
--p-feat-ext--preprocessor TEXT
[default: 'null']
--p-feat-ext--stop-words TEXT
[default: 'null']
--p-feat-ext--strip-accents TEXT
[default: 'null']
--p-feat-ext--token-pattern TEXT
[default: '(?u)\\b\\w\\w+\\b']
--p-feat-ext--tokenizer TEXT
[default: 'null']
--p-verbose / --p-no-verbose
[default: False]
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_naive_bayes
Docstring:
Train the naive_bayes classifier Create a scikit-learn naive_bayes classifier for reads Parameters ---------- reference_reads : FeatureData[Sequence] reference_taxonomy : FeatureData[Taxonomy] class_weight : FeatureTable[RelativeFrequency], optional classify__alpha : Float, optional classify__chunk_size : Int, optional classify__class_prior : Str, optional classify__fit_prior : Bool, optional feat_ext__alternate_sign : Bool, optional feat_ext__analyzer : Str, optional feat_ext__binary : Bool, optional feat_ext__decode_error : Str, optional feat_ext__encoding : Str, optional feat_ext__input : Str, optional feat_ext__lowercase : Bool, optional feat_ext__n_features : Int, optional feat_ext__ngram_range : Str, optional feat_ext__norm : Str, optional feat_ext__preprocessor : Str, optional feat_ext__stop_words : Str, optional feat_ext__strip_accents : Str, optional feat_ext__token_pattern : Str, optional feat_ext__tokenizer : Str, optional verbose : Bool, optional Returns ------- classifier : TaxonomicClassifier