ml_classification
statistics-classification_machinelearning/ml-classification
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flowchart TD 0["ℹ️ Input Dataset\ntrain_rows.csv"]; style 0 stroke:#2c3143,stroke-width:4px; 1["ℹ️ Input Dataset\ntest_rows_labels.csv"]; style 1 stroke:#2c3143,stroke-width:4px; 2["ℹ️ Input Dataset\ntest_rows.csv"]; style 2 stroke:#2c3143,stroke-width:4px; 3["Pipeline Builder"]; 4["Generalized linear models"]; 0 -->|output| 4; 0 -->|output| 4; 5["Nearest Neighbors Classification"]; 0 -->|output| 5; 0 -->|output| 5; 6["Support vector machines SVMs"]; 0 -->|output| 6; 0 -->|output| 6; 7["Ensemble methods"]; 0 -->|output| 7; 0 -->|output| 7; 8["Remove beginning"]; 1 -->|output| 8; 9["Hyperparameter Search"]; 3 -->|outfile| 9; 0 -->|output| 9; 0 -->|output| 9; 10["Generalized linear models"]; 2 -->|output| 10; 4 -->|outfile_fit| 10; 11["Nearest Neighbors Classification"]; 2 -->|output| 11; 5 -->|outfile_fit| 11; 12["Support vector machines SVMs"]; 2 -->|output| 12; 6 -->|outfile_fit| 12; 13["Ensemble methods"]; 2 -->|output| 13; 7 -->|outfile_fit| 13; 14["Ensemble methods"]; 2 -->|output| 14; 9 -->|outfile_object| 14; 15["Plot confusion matrix, precision, recall and ROC and AUC curves"]; 8 -->|out_file1| 15; 10 -->|outfile_predict| 15; 4 -->|outfile_fit| 15; 16["Plot confusion matrix, precision, recall and ROC and AUC curves"]; 1 -->|output| 16; 11 -->|outfile_predict| 16; 5 -->|outfile_fit| 16; 17["Plot confusion matrix, precision, recall and ROC and AUC curves"]; 1 -->|output| 17; 12 -->|outfile_predict| 17; 6 -->|outfile_fit| 17; 18["Plot confusion matrix, precision, recall and ROC and AUC curves"]; 1 -->|output| 18; 13 -->|outfile_predict| 18; 7 -->|outfile_fit| 18; 19["Plot confusion matrix, precision, recall and ROC and AUC curves"]; 1 -->|output| 19; 14 -->|outfile_predict| 19; 9 -->|outfile_object| 19;
Inputs
Input | Label |
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Input dataset | train_rows.csv |
Input dataset | test_rows_labels.csv |
Input dataset | test_rows.csv |
Outputs
From | Output | Label |
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Tools
To use these workflows in Galaxy you can either click the links to download the workflows, or you can right-click and copy the link to the workflow which can be used in the Galaxy form to import workflows.
Importing into Galaxy
Below are the instructions for importing these workflows directly into your Galaxy server of choice to start using them!Hands-on: Importing a workflow
- Click on Workflow on the top menu bar of Galaxy. You will see a list of all your workflows.
- Click on galaxy-upload Import at the top-right of the screen
- Provide your workflow
- Option 1: Paste the URL of the workflow into the box labelled “Archived Workflow URL”
- Option 2: Upload the workflow file in the box labelled “Archived Workflow File”
- Click the Import workflow button
Below is a short video demonstrating how to import a workflow from GitHub using this procedure:
Version History
Version | Commit | Time | Comments |
---|---|---|---|
10 | 291c62626 | 2024-09-12 08:20:56 | Add license |
9 | 328755cfa | 2024-09-11 07:29:35 | Add files via upload |
8 | 6439ff1d5 | 2024-05-21 08:55:18 | rename workflow file and add workflow test |
7 | 502f6e650 | 2024-05-21 08:46:08 | rename workflow file and add workflow test |
6 | e6df909ee | 2024-05-17 09:30:13 | update workflows due to tool upgrade |
5 | bdfa0296c | 2020-04-30 13:14:45 | Update ml_classification.ga |
4 | 2680ad593 | 2020-04-30 10:48:21 | some fixes |
3 | becca5c27 | 2020-04-29 17:36:49 | tags and annotation are added to workflow |
2 | 0da8a889e | 2020-04-29 17:22:58 | workflow format is changed |
1 | 28d2cd66b | 2020-04-29 16:59:10 | workflow is added |
For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/statistics/tutorials/classification_machinelearning/workflows/ml_classification.ga -O workflow.ga workflow-to-tools -w workflow.ga -o tools.yaml shed-tools install -g GALAXY -a API_KEY -t tools.yaml workflow-install -g GALAXY -a API_KEY -w workflow.ga --publish-workflows