# HG changeset patch # User q2d2 # Date 1661804827 0 # Node ID 7ff143a32481a7f5ced592203e4b6d6d5f84c219 planemo upload for repository https://github.com/qiime2/galaxy-tools/tree/main/tools/suite_qiime2__sample_classifier commit 9023cfd83495a517fbcbb6f91d5b01a6f1afcda1 diff -r 000000000000 -r 7ff143a32481 qiime2__sample_classifier__predict_classification.xml --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/qiime2__sample_classifier__predict_classification.xml Mon Aug 29 20:27:07 2022 +0000 @@ -0,0 +1,80 @@ + + + + + Use trained classifier to predict target values for new samples. + + quay.io/qiime2/core:2022.8 + + q2galaxy version sample_classifier + q2galaxy run sample_classifier predict_classification '$inputs' + + + + + + + + + hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['FeatureTable[Frequency]'] + + + + + + hasattr(value.metadata, "semantic_type") and value.metadata.semantic_type in ['SampleEstimator[Classifier]'] + +
+ +
+
+ + + + + + +QIIME 2: sample-classifier predict-classification +================================================= +Use trained classifier to predict target values for new samples. + + +Outputs: +-------- +:predictions.qza: Predicted target values for each input sample. +:probabilities.qza: Predicted class probabilities for each input sample. + +| + +Description: +------------ +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. + + +| + + + + 10.21105/joss.00934 + @article{cite2, + author = {Pedregosa, Fabian and Varoquaux, Gaël and Gramfort, Alexandre and Michel, Vincent and Thirion, Bertrand and Grisel, Olivier and Blondel, Mathieu and Prettenhofer, Peter and Weiss, Ron and Dubourg, Vincent and Vanderplas, Jake and Passos, Alexandre and Cournapeau, David and Brucher, Matthieu and Perrot, Matthieu and Duchesnay, Édouard}, + journal = {Journal of machine learning research}, + number = {Oct}, + pages = {2825--2830}, + title = {Scikit-learn: Machine learning in Python}, + volume = {12}, + year = {2011} +} + + 10.1038/s41587-019-0209-9 + +
diff -r 000000000000 -r 7ff143a32481 test-data/.gitkeep