| Previous changeset 1:fba2a1dc2e30 (2023-01-13) Next changeset 3:b89a29409daa (2024-04-25) |
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Commit message:
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 65e4952f33eb335528e8553150e9097e5ea8f556 |
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modified:
qiime2__sample_classifier__regress_samples_ncv.xml |
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| diff -r fba2a1dc2e30 -r e6d86f57fe1a qiime2__sample_classifier__regress_samples_ncv.xml --- a/qiime2__sample_classifier__regress_samples_ncv.xml Fri Jan 13 23:00:45 2023 +0000 +++ b/qiime2__sample_classifier__regress_samples_ncv.xml Thu Jun 08 19:51:39 2023 +0000 |
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| @@ -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 regress-samples-ncv" id="qiime2__sample_classifier__regress_samples_ncv" version="2022.11.1+q2galaxy.2022.11.1.2" profile="22.05" license="BSD-3-Clause"> +<tool name="qiime2 sample-classifier regress-samples-ncv" id="qiime2__sample_classifier__regress_samples_ncv" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause"> <description>Nested cross-validated supervised learning regressor.</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 regress_samples_ncv '$inputs'</command> @@ -50,11 +50,12 @@ <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('RandomForestRegressor', 'ExtraTreesRegressor', 'GradientBoostingRegressor', 'AdaBoostRegressor', 'ElasticNet', 'Ridge', 'Lasso', 'KNeighborsRegressor', 'LinearSVR', 'SVR')"> + <param name="estimator" type="select" label="estimator: Str % Choices('RandomForestRegressor', 'ExtraTreesRegressor', 'GradientBoostingRegressor', 'AdaBoostRegressor[DecisionTree]', 'AdaBoostRegressor[ExtraTrees]', 'ElasticNet', 'Ridge', 'Lasso', 'KNeighborsRegressor', 'LinearSVR', 'SVR')"> <option value="RandomForestRegressor" selected="true">RandomForestRegressor</option> <option value="ExtraTreesRegressor">ExtraTreesRegressor</option> <option value="GradientBoostingRegressor">GradientBoostingRegressor</option> - <option value="AdaBoostRegressor">AdaBoostRegressor</option> + <option value="AdaBoostRegressor__ob__DecisionTree__cb__">AdaBoostRegressor[DecisionTree]</option> + <option value="AdaBoostRegressor__ob__ExtraTrees__cb__">AdaBoostRegressor[ExtraTrees]</option> <option value="ElasticNet">ElasticNet</option> <option value="Ridge">Ridge</option> <option value="Lasso">Lasso</option> |