Mercurial > repos > bgruening > sklearn_stacking_ensemble_models

diff stacking_ensembles.xml @ 10:ac40a2fe5750 draft

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"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit e2a5eade6d0e5ddf3a47630381a0ad90d80e8a04"
author bgruening
date Tue, 13 Apr 2021 17:21:05 +0000
parents a2e4a45c6083
children
line wrap: on
line diff
--- a/stacking_ensembles.xml	Thu Oct 01 19:54:05 2020 +0000
+++ b/stacking_ensembles.xml	Tue Apr 13 17:21:05 2021 +0000
@@ -1,10 +1,10 @@
-<tool id="sklearn_stacking_ensemble_models" name="Stacking Ensembles" version="@VERSION@">
+<tool id="sklearn_stacking_ensemble_models" name="Stacking Ensembles" version="@VERSION@" profile="20.05">
     <description>builds stacking, voting ensemble models with numerous base options</description>
     <macros>
         <import>main_macros.xml</import>
     </macros>
-    <expand macro="python_requirements"/>
-    <expand macro="macro_stdio"/>
+    <expand macro="python_requirements" />
+    <expand macro="macro_stdio" />
     <version_command>echo "$ENSEMBLE_VERSION"</version_command>
     <command>
         <![CDATA[
@@ -54,63 +54,62 @@
                         <option value="hard" selected="true">hard</option>
                         <option value="soft">soft</option>
                     </param>
-                    <param argument="flatten_transform" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" help=""/>
+                    <param argument="flatten_transform" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" help="" />
                 </expand>
             </when>
             <when value="sklearn.ensemble_VotingRegressor">
-                <expand macro="stacking_voting_weights"/>
+                <expand macro="stacking_voting_weights" />
             </when>
             <when value="mlxtend.classifier_StackingCVClassifier">
                 <expand macro="stacking_ensemble_inputs">
-                    <expand macro="cv_reduced"/>
-                    <expand macro="shuffle" label="shuffle"/>
-                    <expand macro="random_state" default_value="" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data."/>
-                    <param argument="use_probas" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false"/>
+                    <expand macro="cv_reduced" />
+                    <expand macro="shuffle" label="shuffle" />
+                    <expand macro="random_state" default_value="" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data." />
+                    <param argument="use_probas" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" />
                 </expand>
                 <section name="meta_estimator" title="Meta Estimator" expanded="true">
-                    <expand macro="stacking_base_estimator"/>
+                    <expand macro="stacking_base_estimator" />
                 </section>
             </when>
             <when value="mlxtend.classifier_StackingClassifier">
                 <expand macro="stacking_ensemble_inputs">
-                    <param argument="use_probas" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false"/>
-                    <param argument="average_probas" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false"/>
+                    <param argument="use_probas" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" />
+                    <param argument="average_probas" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="false" />
                 </expand>
                 <section name="meta_estimator" title="Meta Estimator" expanded="true">
-                    <expand macro="stacking_base_estimator"/>
+                    <expand macro="stacking_base_estimator" />
                 </section>
             </when>
             <when value="mlxtend.regressor_StackingCVRegressor">
                 <expand macro="stacking_ensemble_inputs">
-                    <expand macro="cv_reduced"/>
+                    <expand macro="cv_reduced" />
                     <!--TODO support group splitters. Hint: `groups` is a fit_param-->
-                    <expand macro="shuffle" label="shuffle"/>
-                    <expand macro="random_state" default_value="" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data."/>
-                    <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true"/>
+                    <expand macro="shuffle" label="shuffle" />
+                    <expand macro="random_state" default_value="" help_text="Integer number. The seed of the pseudo random number generator to use when shuffling the data." />
+                    <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" />
                 </expand>
                 <section name="meta_estimator" title="Meta Estimator" expanded="true">
-                    <expand macro="stacking_base_estimator"/>
+                    <expand macro="stacking_base_estimator" />
                 </section>
             </when>
             <when value="mlxtend.regressor_StackingRegressor">
                 <expand macro="stacking_ensemble_inputs">
-                    <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true"/>
+                    <param argument="refit" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" />
                 </expand>
                 <section name="meta_estimator" title="Meta Estimator" expanded="true">
-                    <expand macro="stacking_base_estimator"/>
+                    <expand macro="stacking_base_estimator" />
                 </section>
             </when>
         </conditional>
         <repeat name="base_est_builder" min="1" max="20" title="Base Estimator">
-            <expand macro="stacking_base_estimator"/>
+            <expand macro="stacking_base_estimator" />
             <!--param name="base_estimator" type="data" format="zip,json" label="Select the dataset containing base estimator" help="One estimator at a time."/-->
         </repeat>
         <!--param name="meta_estimator" type="data" format="zip,json" label="Select the dataset containing the Meta estimator"/-->
-        <param name="get_params" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Output parameters for searchCV?"
-                help="Optional. Tunable parameters could be obtained through `estimator_attributes` tool."/>
+        <param name="get_params" type="boolean" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Output parameters for searchCV?" help="Optional. Tunable parameters could be obtained through `estimator_attributes` tool." />
     </inputs>
     <outputs>
-        <data format="zip" name="outfile" label="${algo_selection.estimator_type} on ${on_string}"/>
+        <data format="zip" name="outfile" label="${algo_selection.estimator_type} on ${on_string}" />
         <data format="tabular" name="outfile_params" label="get_params for ${algo_selection.estimator_type}">
             <filter>get_params</filter>
         </data>
@@ -118,75 +117,75 @@
     <tests>
         <test>
             <conditional name="algo_selection">
-                <param name="estimator_type" value="sklearn.ensemble_VotingClassifier"/>
+                <param name="estimator_type" value="sklearn.ensemble_VotingClassifier" />
                 <section name="options">
-                    <param name="weights" value="[1, 2]"/>
+                    <param name="weights" value="[1, 2]" />
                 </section>
             </conditional>
             <repeat name="base_est_builder">
                 <conditional name="estimator_selector">
-                    <param name="selected_module" value="svm"/>
-                    <param name="selected_estimator" value="SVC"/>
+                    <param name="selected_module" value="svm" />
+                    <param name="selected_estimator" value="SVC" />
                 </conditional>
             </repeat>
             <repeat name="base_est_builder">
                 <conditional name="estimator_selector">
-                    <param name="selected_module" value="xgboost"/>
-                    <param name="selected_estimator" value="XGBClassifier"/>
+                    <param name="selected_module" value="xgboost" />
+                    <param name="selected_estimator" value="XGBClassifier" />
                 </conditional>
             </repeat>
-            <param name="get_params" value="false"/>
-            <output name="outfile" file="StackingVoting03.zip" compare="sim_size" delta="5"/>
+            <param name="get_params" value="false" />
+            <output name="outfile" file="StackingVoting03.zip" compare="sim_size" delta="5" />
         </test>
         <test>
             <conditional name="algo_selection">
-                <param name="estimator_type" value="mlxtend.regressor_StackingCVRegressor"/>
+                <param name="estimator_type" value="mlxtend.regressor_StackingCVRegressor" />
                 <section name="meta_estimator">
                     <conditional name="estimator_selector">
-                        <param name="selected_module" value="custom_estimator"/>
-                        <param name="c_estimator" value="LinearRegression01.zip" ftype="zip"/>
+                        <param name="selected_module" value="custom_estimator" />
+                        <param name="c_estimator" value="LinearRegression01.zip" ftype="zip" />
                     </conditional>
                 </section>
             </conditional>
             <repeat name="base_est_builder">
                 <conditional name="estimator_selector">
-                    <param name="selected_module" value="custom_estimator"/>
-                    <param name="c_estimator" value="RandomForestRegressor01.zip" ftype="zip"/>
+                    <param name="selected_module" value="custom_estimator" />
+                    <param name="c_estimator" value="RandomForestRegressor01.zip" ftype="zip" />
                 </conditional>
             </repeat>
             <repeat name="base_est_builder">
                 <conditional name="estimator_selector">
-                    <param name="selected_module" value="custom_estimator"/>
-                    <param name="c_estimator" value="XGBRegressor01.zip" ftype="zip"/>
+                    <param name="selected_module" value="custom_estimator" />
+                    <param name="c_estimator" value="XGBRegressor01.zip" ftype="zip" />
                 </conditional>
             </repeat>
-            <param name="get_params" value="false"/>
-            <output name="outfile" file="StackingCVRegressor01.zip" compare="sim_size" delta="5"/>
+            <param name="get_params" value="false" />
+            <output name="outfile" file="StackingCVRegressor01.zip" compare="sim_size" delta="5" />
         </test>
         <test>
             <conditional name="algo_selection">
-                <param name="estimator_type" value="mlxtend.regressor_StackingRegressor"/>
+                <param name="estimator_type" value="mlxtend.regressor_StackingRegressor" />
                 <section name="meta_estimator">
                     <conditional name="estimator_selector">
-                        <param name="selected_module" value="svm"/>
-                        <param name="selected_estimator" value="SVR"/>
+                        <param name="selected_module" value="svm" />
+                        <param name="selected_estimator" value="SVR" />
                     </conditional>
                 </section>
             </conditional>
             <repeat name="base_est_builder">
                 <conditional name="estimator_selector">
-                    <param name="selected_module" value="custom_estimator"/>
-                    <param name="c_estimator" value="RandomForestRegressor01.zip" ftype="zip"/>
+                    <param name="selected_module" value="custom_estimator" />
+                    <param name="c_estimator" value="RandomForestRegressor01.zip" ftype="zip" />
                 </conditional>
             </repeat>
             <repeat name="base_est_builder">
                 <conditional name="estimator_selector">
-                    <param name="selected_module" value="xgboost"/>
-                    <param name="selected_estimator" value="XGBRegressor"/>
+                    <param name="selected_module" value="xgboost" />
+                    <param name="selected_estimator" value="XGBRegressor" />
                 </conditional>
             </repeat>
-            <param name="get_params" value="false"/>
-            <output name="outfile" file="StackingRegressor02.zip" compare="sim_size" delta="5"/>
+            <param name="get_params" value="false" />
+            <output name="outfile" file="StackingRegressor02.zip" compare="sim_size" delta="5" />
         </test>
     </tests>
     <help>
@@ -202,9 +201,9 @@
         ]]>
     </help>
     <expand macro="sklearn_citation">
-        <expand macro="skrebate_citation"/>
-        <expand macro="xgboost_citation"/>
-        <expand macro="imblearn_citation"/>
+        <expand macro="skrebate_citation" />
+        <expand macro="xgboost_citation" />
+        <expand macro="imblearn_citation" />
         <citation type="bibtex">
             @article{raschkas_2018_mlxtend,
                 author       = {Sebastian Raschka},