comparison qiime2/qiime_sample-classifier_predict-classification.xml @ 0:370e0b6e9826 draft

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0:370e0b6e9826

<?xml version="1.0" ?>
<tool id="qiime_sample-classifier_predict-classification" name="qiime sample-classifier predict-classification" version="2019.4">
	<description> - Use trained classifier to predict target values for new samples.</description>
	<requirements>
		<requirement type="package" version="2019.4">qiime2</requirement>
	</requirements>
	<command><![CDATA[
qiime sample-classifier predict-classification

--i-table=$itable
--i-sample-estimator=$isampleestimator

#set $pnjobs = '${GALAXY_SLOTS:-4}'

#if str($pnjobs):
 --p-n-jobs="$pnjobs"
#end if

--o-predictions=opredictions
;
cp opredictions.qza $opredictions
	]]></command>
	<inputs>
		<param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction.                  [required]" name="itable" optional="False" type="data"/>
		<param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Classifier] Sample classifier trained with fit_classifier. [required]" name="isampleestimator" optional="False" type="data"/>
	</inputs>
	<outputs>
		<data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions"/>
	</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.

Returns
-------
predictions : SampleData[ClassifierPredictions]
    Predicted target values for each input sample.
	]]></help>
<macros>
    <import>qiime_citation.xml</import>
</macros>
<expand macro="qiime_citation"/>
</tool>