Regression GradientBoosting
statistics-classification_regression/regression-gradientboosting
Launch in Tutorial Mode
question
galaxy-download Download
galaxy-download Download
flowchart TD 0["ℹ️ Input Dataset\nbody_fat_test"]; style 0 stroke:#2c3143,stroke-width:4px; 1["ℹ️ Input Dataset\nbody_fat_train"]; style 1 stroke:#2c3143,stroke-width:4px; 2["ℹ️ Input Dataset\nbody_fat_test_labels"]; style 2 stroke:#2c3143,stroke-width:4px; 3["Ensemble methods"]; 1 -->|output| 3; 1 -->|output| 3; 4["Ensemble methods"]; 0 -->|output| 4; 3 -->|outfile_fit| 4; 5["Plot actual vs predicted curves and residual plots"]; 4 -->|outfile_predict| 5; 2 -->|output| 5; cf1a5f94-f79d-4d13-b142-c3e20e25b658["Output\noutput_scatter_plot"]; 5 --> cf1a5f94-f79d-4d13-b142-c3e20e25b658; style cf1a5f94-f79d-4d13-b142-c3e20e25b658 stroke:#2c3143,stroke-width:4px; e86ba3fd-3f85-4ba9-ad66-4c1e5caa875a["Output\noutput_actual_vs_pred"]; 5 --> e86ba3fd-3f85-4ba9-ad66-4c1e5caa875a; style e86ba3fd-3f85-4ba9-ad66-4c1e5caa875a stroke:#2c3143,stroke-width:4px; 2cbc04d3-d2d9-4623-b63d-51f1b024d611["Output\noutput_residual_plot"]; 5 --> 2cbc04d3-d2d9-4623-b63d-51f1b024d611; style 2cbc04d3-d2d9-4623-b63d-51f1b024d611 stroke:#2c3143,stroke-width:4px;
Inputs
Input | Label |
---|---|
Input dataset | body_fat_test |
Input dataset | body_fat_train |
Input dataset | body_fat_test_labels |
Outputs
From | Output | Label |
---|---|---|
Input dataset | body_fat_test | |
Input dataset | body_fat_train | |
Input dataset | body_fat_test_labels | |
toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_ensemble/sklearn_ensemble/1.0.8.1 | Ensemble methods | |
toolshed.g2.bx.psu.edu/repos/bgruening/plotly_regression_performance_plots/plotly_regression_performance_plots/0.1 | Plot actual vs predicted curves and residual plots |
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:
Video: Importing a workflow from URL
Version History
Version | Commit | Time | Comments |
---|---|---|---|
6 | 4e0ed121f | 2020-05-27 02:24:23 | add labels to workflow_outputs for regression_GradientBoosting.ga, add test from usegalaxy-eu/workflow-testing with updated labels and input sources |
5 | 667ff3de9 | 2020-01-22 10:59:29 | annotation |
4 | eb4d724e0 | 2020-01-15 10:41:35 | Workflow renaming |
3 | 9f881ab87 | 2020-01-09 16:52:34 | checking ML tutorials, updating workflows |
2 | faf6d298a | 2019-12-12 13:02:33 | unflatten workflows |
1 | 0ccef31bb | 2019-06-17 21:55:56 | Update workflows |
For Admins
Installing the workflow tools
wget https://training.galaxyproject.org/training-material/topics/statistics/tutorials/classification_regression/workflows/regression_GradientBoosting.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