view qiime2__feature_classifier__fit_classifier_sklearn.xml @ 2:651c5518951f draft

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__feature_classifier commit 65e4952f33eb335528e8553150e9097e5ea8f556
author q2d2
date Thu, 08 Jun 2023 19:43:40 +0000
parents e736fe382938
children 3c9fe85c41ed
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<?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: 2023.5.0)
for:
    qiime2 (version: 2023.5.1)
-->
<tool name="qiime2 feature-classifier fit-classifier-sklearn" id="qiime2__feature_classifier__fit_classifier_sklearn" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause">
    <description>Train an almost arbitrary scikit-learn classifier</description>
    <requirements>
        <container type="docker">quay.io/qiime2/core:2023.5</container>
    </requirements>
    <version_command>q2galaxy version feature_classifier</version_command>
    <command detect_errors="exit_code">q2galaxy run feature_classifier fit_classifier_sklearn '$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>
        <param name="classifier_specification" type="text" label="classifier_specification: Str" help="[required]">
            <sanitizer>
                <valid initial="string.printable"/>
            </sanitizer>
            <validator type="expression" message="Please verify this parameter.">value is not None and len(value) &gt; 0</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>
        </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-sklearn
==================================================
Train an almost arbitrary scikit-learn classifier


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

|  

Description:
------------
Train a scikit-learn classifier to classify 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>