# HG changeset patch
# User q2d2
# Date 1686253915 0
# Node ID f31f3c575d7e4c3f981716f22c395b85165e3ec2
# Parent  71cd01b7a74f6316faff1c888357d3030e2956f4
planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 65e4952f33eb335528e8553150e9097e5ea8f556

diff -r 71cd01b7a74f -r f31f3c575d7e qiime2__sample_classifier__fit_classifier.xml
--- 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>