Mercurial > repos > q2d2 > qiime2__sample_classifier__fit_classifier
diff qiime2__sample_classifier__fit_classifier.xml @ 2:f31f3c575d7e draft
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 65e4952f33eb335528e8553150e9097e5ea8f556
author | q2d2 |
---|---|
date | Thu, 08 Jun 2023 19:51:55 +0000 |
parents | 71cd01b7a74f |
children | 431ccbdd8582 |
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--- a/qiime2__sample_classifier__fit_classifier.xml Fri Jan 13 23:00:01 2023 +0000 +++ b/qiime2__sample_classifier__fit_classifier.xml Thu Jun 08 19:51:55 2023 +0000 @@ -6,14 +6,14 @@ --> <!-- This tool was automatically generated by: - q2galaxy (version: 2022.11.1) + q2galaxy (version: 2023.5.0) for: - qiime2 (version: 2022.11.1) + qiime2 (version: 2023.5.1) --> -<tool name="qiime2 sample-classifier fit-classifier" id="qiime2__sample_classifier__fit_classifier" version="2022.11.1+q2galaxy.2022.11.1.2" profile="22.05" license="BSD-3-Clause"> +<tool name="qiime2 sample-classifier fit-classifier" id="qiime2__sample_classifier__fit_classifier" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause"> <description>Fit a supervised learning classifier.</description> <requirements> - <container type="docker">quay.io/qiime2/core:2022.11</container> + <container type="docker">quay.io/qiime2/core:2023.5</container> </requirements> <version_command>q2galaxy version sample_classifier</version_command> <command detect_errors="exit_code">q2galaxy run sample_classifier fit_classifier '$inputs'</command> @@ -51,11 +51,12 @@ <param name="random_state" type="integer" optional="true" label="random_state: Int" help="[optional] Seed used by random number generator."/> <param name="n_jobs" type="integer" value="1" label="n_jobs: Int" help="[default: 1] Number of jobs to run in parallel."/> <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."/> - <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestClassifier', 'ExtraTreesClassifier', 'GradientBoostingClassifier', 'AdaBoostClassifier', 'KNeighborsClassifier', 'LinearSVC', 'SVC')"> + <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestClassifier', 'ExtraTreesClassifier', 'GradientBoostingClassifier', 'AdaBoostClassifier[DecisionTree]', 'AdaBoostClassifier[ExtraTrees]', 'KNeighborsClassifier', 'LinearSVC', 'SVC')"> <option value="RandomForestClassifier" selected="true">RandomForestClassifier</option> <option value="ExtraTreesClassifier">ExtraTreesClassifier</option> <option value="GradientBoostingClassifier">GradientBoostingClassifier</option> - <option value="AdaBoostClassifier">AdaBoostClassifier</option> + <option value="AdaBoostClassifier__ob__DecisionTree__cb__">AdaBoostClassifier[DecisionTree]</option> + <option value="AdaBoostClassifier__ob__ExtraTrees__cb__">AdaBoostClassifier[ExtraTrees]</option> <option value="KNeighborsClassifier">KNeighborsClassifier</option> <option value="LinearSVC">LinearSVC</option> <option value="SVC">SVC</option>