--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/qiime_feature-classifier_classify-sklearn.xml	Thu May 24 02:11:44 2018 -0400
@@ -0,0 +1,102 @@
+<?xml version="1.0" ?>
+<tool id="qiime_feature-classifier_classify-sklearn" name="qiime feature-classifier classify-sklearn" version="2018.4">
+	<description>- Pre-fitted sklearn-based taxonomy classifier</description>
+	<requirements>
+		<requirement type="package" version="2018.4">qiime2</requirement>
+	</requirements>
+	<command><![CDATA[
+  qiime feature-classifier classify-sklearn
+
+  #if str( $id_to_classifier_fp.selector ) == 'history'
+  	#set $classifier = $id_to_classifier_fp.classifier_fp
+  	--i-classifier '$classifier'
+  #else:
+  	#set $classifier = $id_to_classifier_fp.classifier.fields.path
+  	--i-classifier '$classifier'
+  #end if
+  
+  	--i-reads=$ireads
+  
+    #if str($pconfidence) != '':
+      #if float($pconfidence) >= 0.0:
+        --p-confidence=$pconfidence
+      #end if
+    #end if
+  
+  #if str($preadorientation) != 'None':
+    --p-read-orientation=$preadorientation
+  #end if
+  
+  #if str($cmdconfig) != 'None':
+   --cmd-config=$cmdconfig
+  #end if
+  
+  #set $pnjobs = '${GALAXY_SLOTS:-4}'
+   --p-n-jobs="$pnjobs"
+   --o-classification=oclassification;
+   
+  cp oclassification.qza $oclassification;
+  ]]></command>
+	<inputs>
+		<param format="qza,no_unzip.zip" label="--i-reads: FeatureData[Sequence] The feature data to be classified. [required]" name="ireads" optional="False" type="data"/>
+
+		<conditional name="id_to_classifier_fp" optional="True">
+		   <param name="selector" type="select" label="Reference classifier to query">
+			  <option value="cached">Public classifiers</option>
+			  <option value="history">Classifiers from your history</option>
+		   </param>
+		   <when value="cached">
+			  <param name="classifier_fp" label="Reference classifier" type="select" optional="True">
+				 <options from_data_table="qiime_taxonomy" />
+			  </param>
+		   </when>
+		   <when value="history">
+			  <param name="classifier_fp" type="data" format="qza,no_unzip.zip" label="Reference classifier" optional="True" />
+		   </when>
+		</conditional>
+
+		<param label="--p-confidence: Confidence threshold for limiting taxonomic depth. Provide -1 to disable confidence calculation, or 0 to calculate confidence but not apply it to limit the taxonomic depth of the assignments.  [default: 0.7]" name="pconfidence" optional="True" type="float" value="0.7"/>
+		<param label="--p-read-orientation: [reverse-complement|same] Direction of reads with respect to reference sequences. same will cause reads to be classified unchanged; reverse-complement will cause reads to be reversed and complemented prior to classification. Default is to autodetect based on the confidence estimates for the first 100 reads.  [optional]" name="preadorientation" optional="True" type="select">
+			<option selected="True" value="None">Selection is Optional</option>
+			<option value="reverse-complement">reverse-complement</option>
+			<option value="same">same</option>
+		</param>
+		<param label="--cmd-config: Use config file for command options" name="cmdconfig" optional="True" type="data"/>
+	</inputs>
+	<outputs>
+		<data format="qza" label="${tool.name} on ${on_string}: classification.qza" name="oclassification"/>
+	</outputs>
+	<help><![CDATA[
+Pre-fitted sklearn-based taxonomy classifier
+---------------------------------------------
+
+Classify reads by taxon using a fitted classifier.
+
+Parameters
+----------
+reads : FeatureData[Sequence]
+    The feature data to be classified.
+classifier : TaxonomicClassifier
+    The taxonomic classifier for classifying the reads.
+reads_per_batch : Int % Range(0, None), optional
+    Number of reads to process in each batch. If 0, this parameter is
+    autoscaled to the number of query sequences / n_jobs.
+pre_dispatch : Str, optional
+    "all" or expression, as in "3*n_jobs". The number of batches (of tasks)
+    to be pre-dispatched.
+confidence : Float, optional
+    Confidence threshold for limiting taxonomic depth. Provide -1 to
+    disable confidence calculation, or 0 to calculate confidence but not
+    apply it to limit the taxonomic depth of the assignments.
+read_orientation : Str % Choices({'reverse-complement', 'same'}), optional
+    Direction of reads with respect to reference sequences. same will cause
+    reads to be classified unchanged; reverse-complement will cause reads
+    to be reversed and complemented prior to classification. Default is to
+    autodetect based on the confidence estimates for the first 100 reads.
+
+Returns
+-------
+classification : FeatureData[Taxonomy]
+]]>
+	</help>
+</tool>