--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/association_rules.xml	Sat May 01 01:24:32 2021 +0000
@@ -0,0 +1,119 @@
+<tool id="sklearn_mlxtend_association_rules" name="Association rules" version="@VERSION@">
+    <description>Extract frequent itemsets and generate association rules</description>
+    <macros>
+        <import>main_macros.xml</import>
+    </macros>
+    <expand macro="python_requirements"/>
+    <expand macro="macro_stdio"/>
+    <version_command>echo "@VERSION@"</version_command>
+    <command detect_errors="exit_code"><![CDATA[
+        python '$__tool_directory__/association_rules.py'
+            --inputs '$inputs'
+            --infile '$infile'
+            --outfile '$outfile'
+            #if $support
+            --support '$support'
+            #end if
+            #if $confidence
+            --confidence '$confidence'
+            #end if
+            #if $lift
+            --lift '$lift'
+            #end if
+            #if $conviction
+            --conviction '$conviction'
+            #end if
+            #if $length
+            --length '$length'
+            #end if
+    ]]>
+    </command>
+    <configfiles>
+        <inputs name="inputs" />
+    </configfiles>
+    <inputs>
+        <param name="infile" type="data" format="tabular" label="Input file"/>
+        <param name="header0" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="true" label="Does the dataset contain header?"/>
+        <param name="support" type="float" optional="true" label="Minimum support"/>
+        <param name="confidence" type="float" optional="true" label="Minimum confidence"/>
+        <param name="lift" type="float" optional="true" label="Minimum lift"/>
+        <param name="conviction" type="float" optional="true" label="Minimum conviction"/>
+        <param name="length" type="integer" optional="true" label="Maximum length"/>
+    </inputs>
+    <outputs>
+        <data name="outfile" format="tabular"/>
+    </outputs>
+    <tests>
+        <test>
+            <param name="infile" value="mba_input_str_w.tabular" ftype="tabular"/>
+            <param name="header0" value="true"/>
+            <param name="support" value="0.5"/>
+            <param name="confidence" value="0.5"/>
+            <param name="lift" value="1.1"/>
+            <param name="conviction" value="1.1"/>
+            <param name="length" value="5"/>
+            <output name="outfile" file="mba_out_str.tabular" ftype="tabular"/>
+        </test>
+        <test>
+            <param name="infile" value="mba_input_int_w.tabular" ftype="tabular"/>
+            <param name="header0" value="true"/>
+            <param name="support" value="0.5"/>
+            <param name="confidence" value="0.5"/>
+            <param name="lift" value="1.1"/>
+            <param name="conviction" value="1.1"/>
+            <param name="length" value="5"/>
+            <output name="outfile" file="mba_output_int.tabular" ftype="tabular"/>
+        </test>
+        <test>
+            <param name="infile" value="mba_input_str_wo.tabular" ftype="tabular"/>
+            <param name="header0" value="false"/>
+            <param name="support" value="0.5"/>
+            <param name="confidence" value="0.5"/>
+            <param name="lift" value="1.1"/>
+            <param name="conviction" value="1.1"/>
+            <param name="length" value="5"/>
+            <output name="outfile" file="mba_output_str.tabular" ftype="tabular"/>
+        </test>
+        <test>
+            <param name="infile" value="mba_input_int_wo.tabular" ftype="tabular"/>
+            <param name="header0" value="false"/>
+            <param name="support" value="0.5"/>
+            <param name="confidence" value="0.5"/>
+            <param name="lift" value="1.1"/>
+            <param name="conviction" value="1.1"/>
+            <param name="length" value="5"/>
+            <output name="outfile" file="mba_output_int.tabular" ftype="tabular"/>
+        </test>
+    </tests>
+    <help><![CDATA[
+**What it does**
+
+Extract frequent itemsets and generate association rules
+
+from mlxtend.frequent_patterns import fpgrowth
+
+Extracts frequent itemsets for association rule mining. An itemset is considered as "frequent" if it 
+meets a user-specified support threshold. For instance, if the support threshold is set to 0.5 (50%), 
+a frequent itemset is defined as a set of items that occur together in at least 50% of all transactions 
+in the database. We can only get itemsets that have a maximum number of items via length input parameter.
+
+from mlxtend.frequent_patterns import association_rules
+
+Generates association rules from frequent itemsets. Rule generation is a common task in the mining of 
+frequent patterns. An association rule is an implication expression of the form X->Y, where X and Y 
+are disjoint itemsets. A more concrete example based on consumer behaviour would be {Diapers}->{Beer} 
+suggesting that people who buy diapers are also likely to buy beer. To evaluate the "interest" of 
+such an association rule, different metrics have been developed, e.g., confidence, lift, and conviction.
+
+Arguments
+
+infile: Each line in infile contains (tab-separated) items in a tranasaction. Different lines/transactions 
+can have differnt/varying number of items.
+
+Returns
+
+outfile: A tab separated file, that has an association rule on each line, with various metrics listed.
+
+    ]]></help>
+    <expand macro="sklearn_citation"/>
+</tool>