Mercurial > repos > florianbegusch > qiime2_suite
comparison qiime2/qiime_sample-classifier_predict-regression.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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28:c28331a63dfd | 29:3ba9833030c1 |
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1 <?xml version="1.0" ?> | |
2 <tool id="qiime_sample-classifier_predict-regression" name="qiime sample-classifier predict-regression" | |
3 version="2020.8"> | |
4 <description>Use trained regressor to predict target values for new samples.</description> | |
5 <requirements> | |
6 <requirement type="package" version="2020.8">qiime2</requirement> | |
7 </requirements> | |
8 <command><![CDATA[ | |
9 qiime sample-classifier predict-regression | |
10 | |
11 --i-table=$itable | |
12 | |
13 --i-sample-estimator=$isampleestimator | |
14 | |
15 --p-n-jobs=$pnjobs | |
16 | |
17 --o-predictions=opredictions | |
18 | |
19 #if str($examples) != 'None': | |
20 --examples=$examples | |
21 #end if | |
22 | |
23 ; | |
24 cp opredictions.qza $opredictions | |
25 | |
26 ]]></command> | |
27 <inputs> | |
28 <param format="qza,no_unzip.zip" label="--i-table: ARTIFACT FeatureTable[Frequency] Feature table containing all features that should be used for target prediction. [required]" name="itable" optional="False" type="data" /> | |
29 <param format="qza,no_unzip.zip" label="--i-sample-estimator: ARTIFACT SampleEstimator[Regressor] Sample regressor trained with fit_regressor. [required]" name="isampleestimator" optional="False" type="data" /> | |
30 <param label="--examples: Show usage examples and exit." name="examples" optional="False" type="data" /> | |
31 | |
32 </inputs> | |
33 | |
34 <outputs> | |
35 <data format="qza" label="${tool.name} on ${on_string}: predictions.qza" name="opredictions" /> | |
36 | |
37 </outputs> | |
38 | |
39 <help><![CDATA[ | |
40 Use trained regressor to predict target values for new samples. | |
41 ############################################################### | |
42 | |
43 Use trained estimator to predict target values for new samples. These will | |
44 typically be unseen samples, e.g., test data (derived manually or from | |
45 split_table) or samples with unknown values, but can theoretically be any | |
46 samples present in a feature table that contain overlapping features with | |
47 the feature table used to train the estimator. | |
48 | |
49 Parameters | |
50 ---------- | |
51 table : FeatureTable[Frequency] | |
52 Feature table containing all features that should be used for target | |
53 prediction. | |
54 sample_estimator : SampleEstimator[Regressor] | |
55 Sample regressor trained with fit_regressor. | |
56 n_jobs : Int, optional | |
57 Number of jobs to run in parallel. | |
58 | |
59 Returns | |
60 ------- | |
61 predictions : SampleData[RegressorPredictions] | |
62 Predicted target values for each input sample. | |
63 ]]></help> | |
64 <macros> | |
65 <import>qiime_citation.xml</import> | |
66 </macros> | |
67 <expand macro="qiime_citation"/> | |
68 </tool> |