annotate qiime2__feature_classifier__fit_classifier_naive_bayes.xml @ 1:42f3a9cab210 draft

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__feature_classifier commit 69da7976573cc07a363ac66bdacc9269d7cd3732

<?xml version='1.0' encoding='utf-8'?>
<!--
Copyright (c) 2023, QIIME 2 development team.

Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause)
-->
<!--
This tool was automatically generated by:
    q2galaxy (version: 2022.11.1)
for:
    qiime2 (version: 2022.11.1)
-->
<tool name="qiime2 feature-classifier fit-classifier-naive-bayes" id="qiime2__feature_classifier__fit_classifier_naive_bayes" version="2022.11.1+q2galaxy.2022.11.1.2" profile="22.05" license="BSD-3-Clause">
    <description>Train the naive_bayes classifier</description>
    <requirements>
        <container type="docker">quay.io/qiime2/core:2022.11</container>
    </requirements>
    <version_command>q2galaxy version feature_classifier</version_command>
    <command detect_errors="exit_code">q2galaxy run feature_classifier fit_classifier_naive_bayes '$inputs'</command>
    <configfiles>
        <inputs name="inputs" data_style="paths"/>
    </configfiles>
    <inputs>
        <param name="reference_reads" type="data" format="qza" label="reference_reads: FeatureData[Sequence]" help="[required]">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="FeatureData[Sequence]"/>
            </options>
            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureData[Sequence]']</validator>
        </param>
        <param name="reference_taxonomy" type="data" format="qza" label="reference_taxonomy: FeatureData[Taxonomy]" help="[required]">
            <options options_filter_attribute="metadata.semantic_type">
                <filter type="add_value" value="FeatureData[Taxonomy]"/>
            </options>
            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureData[Taxonomy]']</validator>
        </param>
        <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">
            <param name="class_weight" type="data" format="qza" optional="true" label="class_weight: FeatureTable[RelativeFrequency]" help="[optional]">
                <options options_filter_attribute="metadata.semantic_type">
                    <filter type="add_value" value="FeatureTable[RelativeFrequency]"/>
                </options>
                <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[RelativeFrequency]']</validator>
            </param>
            <param name="classify__alpha" type="float" value="0.001" label="classify__alpha: Float" help="[default: 0.001]"/>
            <param name="classify__chunk_size" type="integer" value="20000" label="classify__chunk_size: Int" help="[default: 20000]"/>
            <param name="classify__class_prior" type="text" value="null" label="classify__class_prior: Str" help="[default: 'null']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="classify__fit_prior" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="classify__fit_prior: Bool" help="[default: No]"/>
            <param name="feat_ext__alternate_sign" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="feat_ext__alternate_sign: Bool" help="[default: No]"/>
            <param name="feat_ext__analyzer" type="text" value="char_wb" label="feat_ext__analyzer: Str" help="[default: 'char_wb']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__binary" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="feat_ext__binary: Bool" help="[default: No]"/>
            <param name="feat_ext__decode_error" type="text" value="strict" label="feat_ext__decode_error: Str" help="[default: 'strict']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__encoding" type="text" value="utf-8" label="feat_ext__encoding: Str" help="[default: 'utf-8']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__input" type="text" value="content" label="feat_ext__input: Str" help="[default: 'content']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__lowercase" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" checked="true" label="feat_ext__lowercase: Bool" help="[default: Yes]"/>
            <param name="feat_ext__n_features" type="integer" value="8192" label="feat_ext__n_features: Int" help="[default: 8192]"/>
            <param name="feat_ext__ngram_range" type="text" value="[7, 7]" label="feat_ext__ngram_range: Str" help="[default: '[7, 7]']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__norm" type="text" value="l2" label="feat_ext__norm: Str" help="[default: 'l2']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__preprocessor" type="text" value="null" label="feat_ext__preprocessor: Str" help="[default: 'null']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__stop_words" type="text" value="null" label="feat_ext__stop_words: Str" help="[default: 'null']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__strip_accents" type="text" value="null" label="feat_ext__strip_accents: Str" help="[default: 'null']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__token_pattern" type="text" value="(?u)\b\w\w+\b" label="feat_ext__token_pattern: Str" help="[default: '(?u)\\b\\w\\w+\\b']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="feat_ext__tokenizer" type="text" value="null" label="feat_ext__tokenizer: Str" help="[default: 'null']">
                <sanitizer>
                    <valid initial="string.printable"/>
                </sanitizer>
            </param>
            <param name="verbose" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="verbose: Bool" help="[default: No]"/>
        </section>
    </inputs>
    <outputs>
        <data name="classifier" format="qza" label="${tool.name} on ${on_string}: classifier.qza" from_work_dir="classifier.qza"/>
    </outputs>
    <tests/>
    <help>
QIIME 2: feature-classifier fit-classifier-naive-bayes
======================================================
Train the naive_bayes classifier


Outputs:
--------
:classifier.qza: &lt;no description&gt;

|  

Description:
------------
Create a scikit-learn naive_bayes classifier for reads


|  

</help>
    <citations>
        <citation type="bibtex">@article{cite1,
 author = {Pedregosa, Fabian and Varoquaux, Gaël and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and Vanderplas, Jake and Passos, Alexandre and Cournapeau, David and Brucher, Matthieu and Perrot, Matthieu and Duchesnay, Édouard},
 journal = {Journal of machine learning research},
 number = {Oct},
 pages = {2825--2830},
 title = {Scikit-learn: Machine learning in Python},
 volume = {12},
 year = {2011}
}
</citation>
        <citation type="doi">10.1186/s40168-018-0470-z</citation>
        <citation type="doi">10.1038/s41587-019-0209-9</citation>
    </citations>
</tool>