--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/qiime2-2020.8/qiime_sample-classifier_predict-classification.xml	Thu Sep 03 09:33:04 2020 +0000
@@ -0,0 +1,73 @@
+<?xml version="1.0" ?>
+<tool id="qiime_sample-classifier_predict-classification" name="qiime sample-classifier predict-classification"
+      version="2020.8">
+  <description>Use trained classifier to predict target values for new samples.</description>
+  <requirements>
+    <requirement type="package" version="2020.8">qiime2</requirement>
+  </requirements>
+  <command><![CDATA[
+qiime sample-classifier predict-classification
+
+--i-table=$itable
+
+--i-sample-estimator=$isampleestimator
+
+--p-n-jobs=$pnjobs
+
+--o-predictions=opredictions
+
+--o-probabilities=oprobabilities
+
+#if str($examples) != 'None':
+--examples=$examples
+#end if
+
+;
+cp oprobabilities.qza $oprobabilities
+
+  ]]></command>
+  <inputs>
+    <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction.                  [required]" name="itable" optional="False" type="data" />
+    <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data" />
+    <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" />
+    
+  </inputs>
+
+  <outputs>
+    <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" />
+    <data format="qza" label="${tool.name} on ${on_string}: probabilities.qza" name="oprobabilities" />
+    
+  </outputs>
+
+  <help><![CDATA[
+Use trained classifier to predict target values for new samples.
+###############################################################
+
+Use trained estimator to predict target values for new samples. These will
+typically be unseen samples, e.g., test data (derived manually or from
+split_table) or samples with unknown values, but can theoretically be any
+samples present in a feature table that contain overlapping features with
+the feature table used to train the estimator.
+
+Parameters
+----------
+table : FeatureTable[Frequency]
+    Feature table containing all features that should be used for target
+    prediction.
+sample_estimator : SampleEstimator[Classifier]
+    Sample classifier trained with fit_classifier.
+n_jobs : Int, optional
+    Number of jobs to run in parallel.
+
+Returns
+-------
+predictions : SampleData[ClassifierPredictions]
+    Predicted target values for each input sample.
+probabilities : SampleData[Probabilities]
+    Predicted class probabilities for each input sample.
+  ]]></help>
+  <macros>
+    <import>qiime_citation.xml</import>
+  </macros>
+  <expand macro="qiime_citation"/>
+</tool>
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