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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 389df0134cd0763dcf02aac6e623fc15f8861c1e
author q2d2
date Thu, 25 Apr 2024 21:26:50 +0000
parents 09981e91ac53
children f28bc42125b6
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1 <?xml version='1.0' encoding='utf-8'?> 1 <?xml version='1.0' encoding='utf-8'?>
2 <!-- 2 <!--
3 Copyright (c) 2023, QIIME 2 development team. 3 Copyright (c) 2024, QIIME 2 development team.
4 4
5 Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause) 5 Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause)
6 --> 6 -->
7 <!-- 7 <!--
8 This tool was automatically generated by: 8 This tool was automatically generated by:
9 q2galaxy (version: 2023.5.0) 9 q2galaxy (version: 2024.2.1)
10 for: 10 for:
11 qiime2 (version: 2023.5.1) 11 qiime2 (version: 2024.2.0)
12 --> 12 -->
13 <tool name="qiime2 sample-classifier regress-samples" id="qiime2__sample_classifier__regress_samples" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause"> 13 <tool name="qiime2 sample-classifier regress-samples" id="qiime2__sample_classifier__regress_samples" version="2024.2.0+q2galaxy.2024.2.1" profile="22.05" license="BSD-3-Clause">
14 <description>Train and test a cross-validated supervised learning regressor.</description> 14 <description>Train and test a cross-validated supervised learning regressor.</description>
15 <requirements> 15 <requirements>
16 <container type="docker">quay.io/qiime2/core:2023.5</container> 16 <container type="docker">quay.io/qiime2/amplicon:2024.2</container>
17 </requirements> 17 </requirements>
18 <version_command>q2galaxy version sample_classifier</version_command> 18 <version_command>q2galaxy version sample_classifier</version_command>
19 <command detect_errors="exit_code">q2galaxy run sample_classifier regress_samples '$inputs'</command> 19 <command detect_errors="exit_code">q2galaxy run sample_classifier regress_samples '$inputs'</command>
20 <configfiles> 20 <configfiles>
21 <inputs name="inputs" data_style="paths"/> 21 <inputs name="inputs" data_style="staging_path_and_source_path"/>
22 </configfiles> 22 </configfiles>
23 <inputs> 23 <inputs>
24 <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."> 24 <param name="table" type="data" format="qza" label="table: FeatureTable[Frequency | RelativeFrequency | PresenceAbsence | Composition]" help="[required] Feature table containing all features that should be used for target prediction.">
25 <options options_filter_attribute="metadata.semantic_type"> 25 <options options_filter_attribute="metadata.semantic_type">
26 <filter type="add_value" value="FeatureTable[Composition]"/>
26 <filter type="add_value" value="FeatureTable[Frequency]"/> 27 <filter type="add_value" value="FeatureTable[Frequency]"/>
28 <filter type="add_value" value="FeatureTable[RelativeFrequency]"/>
29 <filter type="add_value" value="FeatureTable[PresenceAbsence]"/>
27 </options> 30 </options>
28 <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Frequency]']</validator> 31 <validator type="expression" message="Incompatible type">hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Composition]', 'FeatureTable[Frequency]', 'FeatureTable[PresenceAbsence]', 'FeatureTable[RelativeFrequency]']</validator>
29 </param> 32 </param>
30 <conditional name="metadata"> 33 <conditional name="metadata">
31 <param name="type" type="select" label="metadata: MetadataColumn[Numeric]" help="[required] Numeric metadata column to use as prediction target."> 34 <param name="type" type="select" label="metadata: MetadataColumn[Numeric]" help="[required] Numeric metadata column to use as prediction target.">
32 <option value="tsv" selected="true">Metadata from TSV</option> 35 <option value="tsv" selected="true">Metadata from TSV</option>
33 <option value="qza">Metadata from Artifact</option> 36 <option value="qza">Metadata from Artifact</option>
48 <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options"> 51 <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options">
49 <param name="test_size" type="float" min="0.0" max="0.999999" value="0.2" label="test_size: Float % Range(0.0, 1.0)" help="[default: 0.2] Fraction of input samples to exclude from training set and use for classifier testing."/> 52 <param name="test_size" type="float" min="0.0" max="0.999999" value="0.2" label="test_size: Float % Range(0.0, 1.0)" help="[default: 0.2] Fraction of input samples to exclude from training set and use for classifier testing."/>
50 <param name="step" type="float" min="1e-06" max="0.999999" value="0.05" label="step: Float % Range(0.0, 1.0, inclusive_start=False)" help="[default: 0.05] If optimize_feature_selection is True, step is the percentage of features to remove at each iteration."/> 53 <param name="step" type="float" min="1e-06" max="0.999999" value="0.05" label="step: Float % Range(0.0, 1.0, inclusive_start=False)" help="[default: 0.05] If optimize_feature_selection is True, step is the percentage of features to remove at each iteration."/>
51 <param name="cv" type="integer" min="1" value="5" label="cv: Int % Range(1, None)" help="[default: 5] Number of k-fold cross-validations to perform."/> 54 <param name="cv" type="integer" min="1" value="5" label="cv: Int % Range(1, None)" help="[default: 5] Number of k-fold cross-validations to perform."/>
52 <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/> 55 <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/>
53 <param name="n_jobs" type="integer" value="1" label="n_jobs: Int" help="[default: 1] Number of jobs to run in parallel."/>
54 <param name="n_estimators" type="integer" min="1" value="100" label="n_estimators: Int % Range(1, None)" help="[default: 100] Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting."/> 56 <param name="n_estimators" type="integer" min="1" value="100" label="n_estimators: Int % Range(1, None)" help="[default: 100] Number of trees to grow for estimation. More trees will improve predictive accuracy up to a threshold level, but will also increase time and memory requirements. This parameter only affects ensemble estimators, such as Random Forest, AdaBoost, ExtraTrees, and GradientBoosting."/>
55 <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestRegressor', 'ExtraTreesRegressor', 'GradientBoostingRegressor', 'AdaBoostRegressor[DecisionTree]', 'AdaBoostRegressor[ExtraTrees]', 'ElasticNet', 'Ridge', 'Lasso', 'KNeighborsRegressor', 'LinearSVR', 'SVR')"> 57 <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestRegressor', 'ExtraTreesRegressor', 'GradientBoostingRegressor', 'AdaBoostRegressor[DecisionTree]', 'AdaBoostRegressor[ExtraTrees]', 'ElasticNet', 'Ridge', 'Lasso', 'KNeighborsRegressor', 'LinearSVR', 'SVR')">
56 <option value="RandomForestRegressor" selected="true">RandomForestRegressor</option> 58 <option value="RandomForestRegressor" selected="true">RandomForestRegressor</option>
57 <option value="ExtraTreesRegressor">ExtraTreesRegressor</option> 59 <option value="ExtraTreesRegressor">ExtraTreesRegressor</option>
58 <option value="GradientBoostingRegressor">GradientBoostingRegressor</option> 60 <option value="GradientBoostingRegressor">GradientBoostingRegressor</option>