diff qiime2__sample_classifier__predict_regression.xml @ 0:b2b6de98d04c draft

planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1

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+++ b/qiime2__sample_classifier__predict_regression.xml	Mon Aug 29 20:29:06 2022 +0000
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+<?xml version='1.0' encoding='utf-8'?>
+<!--
+Copyright (c) 2022, 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: 2022.8.1)
+for:
+    qiime2 (version: 2022.8.1)
+-->
+<tool name="qiime2 sample-classifier predict-regression" id="qiime2__sample_classifier__predict_regression" version="2022.8.0+q2galaxy.2022.8.1.2" profile="22.05" license="BSD-3-Clause">
+    <description>Use trained regressor to predict target values for new samples.</description>
+    <requirements>
+        <container type="docker">quay.io/qiime2/core:2022.8</container>
+    </requirements>
+    <version_command>q2galaxy version sample_classifier</version_command>
+    <command detect_errors="aggressive">q2galaxy run sample_classifier predict_regression '$inputs'</command>
+    <configfiles>
+        <inputs name="inputs" data_style="paths"/>
+    </configfiles>
+    <inputs>
+        <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency]" help="[required]  Feature table containing all features that should be used for target prediction.">
+            <options options_filter_attribute="metadata.semantic_type">
+                <filter type="add_value" value="FeatureTable[Frequency]"/>
+            </options>
+            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Frequency]']</validator>
+        </param>
+        <param name="sample_estimator" type="data" format="qza" label="sample_estimator: SampleEstimator[Regressor]" help="[required]  Sample regressor trained with fit_regressor.">
+            <options options_filter_attribute="metadata.semantic_type">
+                <filter type="add_value" value="SampleEstimator[Regressor]"/>
+            </options>
+            <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['SampleEstimator[Regressor]']</validator>
+        </param>
+        <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">
+            <param name="n_jobs" type="integer" value="1" label="n_jobs: Int" help="[default: 1]  Number of jobs to run in parallel."/>
+        </section>
+    </inputs>
+    <outputs>
+        <data name="predictions" format="qza" label="${tool.name} on ${on_string}: predictions.qza" from_work_dir="predictions.qza"/>
+    </outputs>
+    <tests/>
+    <help>
+QIIME 2: sample-classifier predict-regression
+=============================================
+Use trained regressor to predict target values for new samples.
+
+
+Outputs:
+--------
+:predictions.qza: Predicted target values for each input sample.
+
+|  
+
+Description:
+------------
+Use trained estimator to predict target values for new samples. These will typically be unseen samples, e.g., test data (derived manually or from split_table) or samples with unknown values, but can theoretically be any samples present in a feature table that contain overlapping features with the feature table used to train the estimator.
+
+
+|  
+
+</help>
+    <citations>
+        <citation type="doi">10.21105/joss.00934</citation>
+        <citation type="bibtex">@article{cite2,
+ 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">10.1038/s41587-019-0209-9</citation>
+    </citations>
+</tool>