# HG changeset patch
# User q2d2
# Date 1686253921 0
# Node ID d0708941b20b0be1c2a7eb8b8d1f8a734979dbce
# Parent  c0aa54edd09e597a33ebf9c4f1f8d31a7722172c
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 65e4952f33eb335528e8553150e9097e5ea8f556

diff -r c0aa54edd09e -r d0708941b20b qiime2__sample_classifier__fit_regressor.xml
--- a/qiime2__sample_classifier__fit_regressor.xml	Fri Jan 13 23:00:38 2023 +0000
+++ b/qiime2__sample_classifier__fit_regressor.xml	Thu Jun 08 19:52:01 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-regressor" id="qiime2__sample_classifier__fit_regressor" version="2022.11.1+q2galaxy.2022.11.1.2" profile="22.05" license="BSD-3-Clause">
+<tool name="qiime2 sample-classifier fit-regressor" id="qiime2__sample_classifier__fit_regressor" version="2023.5.0+q2galaxy.2023.5.0.2" profile="22.05" license="BSD-3-Clause">
     <description>Fit a 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 fit_regressor '$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('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>