Mercurial > repos > florianbegusch > qiime2_suite
diff qiime2/qiime_sample-classifier_predict-classification.xml @ 29:3ba9833030c1 draft
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author | florianbegusch |
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date | Fri, 04 Sep 2020 13:12:49 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/qiime2/qiime_sample-classifier_predict-classification.xml Fri Sep 04 13:12:49 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> \ No newline at end of file