Mercurial > repos > q2d2 > qiime2__sample_classifier__regress_samples_ncv
annotate qiime2__sample_classifier__regress_samples_ncv.xml @ 4:629fe9f7d95a draft default tip
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
author | q2d2 |
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date | Mon, 03 Jun 2024 23:32:00 +0000 |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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1 <?xml version='1.0' encoding='utf-8'?> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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2 <!-- |
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3 Copyright (c) 2024, QIIME 2 development team. |
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896b0ff9a810
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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5 Distributed under the terms of the Modified BSD License. (SPDX: BSD-3-Clause) |
896b0ff9a810
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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896b0ff9a810
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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7 <!-- |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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8 This tool was automatically generated by: |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
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9 q2galaxy (version: 2024.5.0) |
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10 for: |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
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11 qiime2 (version: 2024.5.0) |
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12 --> |
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13 <tool name="qiime2 sample-classifier regress-samples-ncv" id="qiime2__sample_classifier__regress_samples_ncv" version="2024.5.0+q2galaxy.2024.5.0" profile="22.05" license="BSD-3-Clause"> |
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14 <description>Nested cross-validated supervised learning regressor.</description> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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15 <requirements> |
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16 <container type="docker">quay.io/qiime2/amplicon:2024.5</container> |
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17 </requirements> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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18 <version_command>q2galaxy version sample_classifier</version_command> |
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19 <command detect_errors="exit_code">q2galaxy run sample_classifier regress_samples_ncv '$inputs'</command> |
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20 <configfiles> |
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21 <inputs name="inputs" data_style="staging_path_and_source_path"/> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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22 </configfiles> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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23 <inputs> |
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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."> |
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25 <options options_filter_attribute="metadata.semantic_type"> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
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26 <filter type="add_value" value="FeatureTable[Frequency]"/> |
629fe9f7d95a
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
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27 <filter type="add_value" value="FeatureTable[PresenceAbsence]"/> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit c7e80dcda727ce63b42aa8a946e9330310929797
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28 <filter type="add_value" value="FeatureTable[RelativeFrequency]"/> |
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29 <filter type="add_value" value="FeatureTable[Composition]"/> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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30 </options> |
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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> |
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planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1
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32 </param> |
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33 <conditional name="metadata"> |
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34 <param name="type" type="select" label="metadata: MetadataColumn[Numeric]" help="[required] Numeric metadata column to use as prediction target."> |
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35 <option value="tsv" selected="true">Metadata from TSV</option> |
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36 <option value="qza">Metadata from Artifact</option> |
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37 </param> |
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38 <when value="tsv"> |
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39 <param name="source" type="data" format="tabular,qiime2.tabular" label="Metadata Source"/> |
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40 <param name="column" type="data_column" label="Column Name" data_ref="source" use_header_names="true"> |
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41 <validator type="expression" message="The first column cannot be selected (they are IDs).">value != "1"</validator> |
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42 </param> |
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43 </when> |
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44 <when value="qza"> |
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45 <param name="source" type="data" format="qza" label="Metadata Source"/> |
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46 <param name="column" type="text" label="Column Name"> |
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47 <validator type="empty_field"/> |
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48 </param> |
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49 </when> |
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50 </conditional> |
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51 <section name="__q2galaxy__GUI__section__extra_opts__" title="Click here for additional options"> |
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52 <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."/> |
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53 <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/> |
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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."/> |
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55 <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestRegressor', 'ExtraTreesRegressor', 'GradientBoostingRegressor', 'AdaBoostRegressor[DecisionTree]', 'AdaBoostRegressor[ExtraTrees]', 'ElasticNet', 'Ridge', 'Lasso', 'KNeighborsRegressor', 'LinearSVR', 'SVR')"> |
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56 <option value="RandomForestRegressor" selected="true">RandomForestRegressor</option> |
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57 <option value="ExtraTreesRegressor">ExtraTreesRegressor</option> |
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58 <option value="GradientBoostingRegressor">GradientBoostingRegressor</option> |
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59 <option value="AdaBoostRegressor__ob__DecisionTree__cb__">AdaBoostRegressor[DecisionTree]</option> |
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60 <option value="AdaBoostRegressor__ob__ExtraTrees__cb__">AdaBoostRegressor[ExtraTrees]</option> |
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61 <option value="ElasticNet">ElasticNet</option> |
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62 <option value="Ridge">Ridge</option> |
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63 <option value="Lasso">Lasso</option> |
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64 <option value="KNeighborsRegressor">KNeighborsRegressor</option> |
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65 <option value="LinearSVR">LinearSVR</option> |
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66 <option value="SVR">SVR</option> |
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67 </param> |
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68 <param name="stratify" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="stratify: Bool" help="[default: No] Evenly stratify training and test data among metadata categories. If True, all values in column must match at least two samples."/> |
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69 <param name="parameter_tuning" type="boolean" truevalue="__q2galaxy__::literal::True" falsevalue="__q2galaxy__::literal::False" label="parameter_tuning: Bool" help="[default: No] Automatically tune hyperparameters using random grid search."/> |
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70 <param name="missing_samples" type="select" label="missing_samples: Str % Choices('error', 'ignore')" display="radio"> |
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71 <option value="error" selected="true">error</option> |
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72 <option value="ignore">ignore</option> |
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73 </param> |
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74 </section> |
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75 </inputs> |
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76 <outputs> |
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77 <data name="predictions" format="qza" label="${tool.name} on ${on_string}: predictions.qza" from_work_dir="predictions.qza"/> |
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78 <data name="feature_importance" format="qza" label="${tool.name} on ${on_string}: feature_importance.qza" from_work_dir="feature_importance.qza"/> |
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79 </outputs> |
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80 <tests/> |
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81 <help> |
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82 QIIME 2: sample-classifier regress-samples-ncv |
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83 ============================================== |
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84 Nested cross-validated supervised learning regressor. |
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85 |
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86 |
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87 Outputs: |
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88 -------- |
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89 :predictions.qza: Predicted target values for each input sample. |
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90 :feature_importance.qza: Importance of each input feature to model accuracy. |
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91 |
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92 | |
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93 |
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94 Description: |
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95 ------------ |
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96 Predicts a continuous sample metadata column using a supervised learning regressor. Uses nested stratified k-fold cross validation for automated hyperparameter optimization and sample prediction. Outputs predicted values for each input sample, and relative importance of each feature for model accuracy. |
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97 |
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98 |
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99 | |
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100 |
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101 </help> |
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102 <citations> |
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103 <citation type="doi">10.21105/joss.00934</citation> |
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104 <citation type="bibtex">@article{cite2, |
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105 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}, |
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106 journal = {Journal of machine learning research}, |
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107 number = {Oct}, |
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108 pages = {2825--2830}, |
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109 title = {Scikit-learn: Machine learning in Python}, |
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110 volume = {12}, |
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111 year = {2011} |
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112 } |
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113 </citation> |
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114 <citation type="doi">10.1038/s41587-019-0209-9</citation> |
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115 </citations> |
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116 </tool> |