Mercurial > repos > bgruening > sklearn_ensemble

diff ensemble.xml @ 23:39ae276e75d9 draft

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planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 57f4407e278a615f47a377a3328782b1d8e0b54d
author bgruening
date Sun, 30 Dec 2018 01:56:11 -0500
parents 2e69c6ca6e91
children e94395c672bd
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line diff
--- a/ensemble.xml	Thu Oct 11 03:34:03 2018 -0400
+++ b/ensemble.xml	Sun Dec 30 01:56:11 2018 -0500
@@ -100,7 +100,7 @@
             <when value="RandomForestClassifier">
                 <expand macro="sl_mixed_input"/>
                 <section name="options" title="Advanced Options" expanded="False">
-                    <expand macro="n_estimators"/>
+                    <expand macro="n_estimators" default_value="100"/>
                     <expand macro="criterion"/>
                     <expand macro="max_features"/>
                     <expand macro="max_depth"/>
@@ -158,7 +158,7 @@
             <when value="RandomForestRegressor">
                 <expand macro="sl_mixed_input"/>
                 <section name="options" title="Advanced Options" expanded="False">
-                    <expand macro="n_estimators"/>
+                    <expand macro="n_estimators" default_value="100"/>
                     <expand macro="criterion2"/>
                     <expand macro="max_features"/>
                     <expand macro="max_depth"/>
@@ -232,13 +232,13 @@
             <param name="selected_task" value="train"/>
             <param name="selected_algorithm" value="RandomForestClassifier"/>
             <param name="random_state" value="10"/>
-            <output name="outfile_fit" file="rfc_model01" compare="sim_size" delta="500"/>
+            <output name="outfile_fit" file="rfc_model01" compare="sim_size" delta="5"/>
         </test>
         <test>
             <param name="infile_model" value="rfc_model01" ftype="zip"/>
             <param name="infile_data" value="test.tabular" ftype="tabular"/>
             <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="rfc_result01" compare="sim_size" delta="500"/>
+            <output name="outfile_predict" file="rfc_result01"/>
         </test>
         <test>
             <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
@@ -248,13 +248,13 @@
             <param name="selected_task" value="train"/>
             <param name="selected_algorithm" value="RandomForestRegressor"/>
             <param name="random_state" value="10"/>
-            <output name="outfile_fit" file="rfr_model01" compare="sim_size" delta="500"/>
+            <output name="outfile_fit" file="rfr_model01" compare="sim_size" delta="5"/>
         </test>
         <test>
             <param name="infile_model" value="rfr_model01" ftype="zip"/>
             <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
             <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="rfr_result01" compare="sim_size" delta="500"/>
+            <output name="outfile_predict" file="rfr_result01"/>
         </test>
         <test>
             <param name="infile1" value="regression_X.tabular" ftype="tabular"/>
@@ -268,14 +268,14 @@
             <param name="max_features" value="number_input"/>
             <param name="num_max_features" value="0.5"/>
             <param name="random_state" value="42"/>
-            <output name="outfile_fit" file="gbr_model01" compare="sim_size" delta="500"/>
+            <output name="outfile_fit" file="gbr_model01" compare="sim_size" delta="5"/>
         </test>
         <test>
             <param name="infile_model" value="gbr_model01" ftype="zip"/>
             <param name="infile_data" value="regression_test_X.tabular" ftype="tabular"/>
             <param name="selected_task" value="load"/>
             <param name="header" value="True"/>
-            <output name="outfile_predict" file="gbr_prediction_result01.tabular" compare="sim_size" delta="500"/>
+            <output name="outfile_predict" file="gbr_prediction_result01.tabular"/>
         </test>
         <test>
             <param name="infile1" value="train.tabular" ftype="tabular"/>
@@ -284,13 +284,13 @@
             <param name="col2" value="5"/>
             <param name="selected_task" value="train"/>
             <param name="selected_algorithm" value="GradientBoostingClassifier"/>
-            <output name="outfile_fit" file="gbc_model01" compare="sim_size" delta="500"/>
+            <output name="outfile_fit" file="gbc_model01" compare="sim_size" delta="5"/>
         </test>
         <test>
             <param name="infile_model" value="gbc_model01" ftype="zip"/>
             <param name="infile_data" value="test.tabular" ftype="tabular"/>
             <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="gbc_result01" compare="sim_size" delta="500"/>
+            <output name="outfile_predict" file="gbc_result01"/>
         </test>
         <test>
             <param name="infile1" value="train.tabular" ftype="tabular"/>
@@ -300,13 +300,13 @@
             <param name="selected_task" value="train"/>
             <param name="selected_algorithm" value="AdaBoostClassifier"/>
             <param name="random_state" value="10"/>
-            <output name="outfile_fit" file="abc_model01" compare="sim_size" delta="500"/>
+            <output name="outfile_fit" file="abc_model01" compare="sim_size" delta="5"/>
         </test>
         <test>
             <param name="infile_model" value="abc_model01" ftype="zip"/>
             <param name="infile_data" value="test.tabular" ftype="tabular"/>
             <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="abc_result01" compare="sim_size" delta="500"/>
+            <output name="outfile_predict" file="abc_result01"/>
         </test>
         <test>
             <param name="infile1" value="regression_train.tabular" ftype="tabular"/>
@@ -316,13 +316,13 @@
             <param name="selected_task" value="train"/>
             <param name="selected_algorithm" value="AdaBoostRegressor"/>
             <param name="random_state" value="10"/>
-            <output name="outfile_fit" file="abr_model01" compare="sim_size" delta="500"/>
+            <output name="outfile_fit" file="abr_model01" compare="sim_size" delta="5"/>
         </test>
         <test>
             <param name="infile_model" value="abr_model01" ftype="zip"/>
             <param name="infile_data" value="regression_test.tabular" ftype="tabular"/>
             <param name="selected_task" value="load"/>
-            <output name="outfile_predict" file="abr_result01" compare="sim_size" delta="500"/>
+            <output name="outfile_predict" file="abr_result01"/>
         </test>
     </tests>
     <help><![CDATA[