Regression GradientBoosting 6.0
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Run on GalaxyMachine learning: classification and regression
Associated Tutorial
This workflows is part of the tutorial Machine learning: classification and regression, available in the GTN
Features
- Includes Galaxy Workflow Tests
Thanks to...
Tutorial Author(s): Anup Kumar, Bérénice Batut
Tutorial Contributor(s): Saskia Hiltemann, Bérénice Batut, Björn Grüning, Alireza Khanteymoori, Helena Rasche, Martin Čech, Armin Dadras
Funder(s): ELIXIR Europe, de.NBI, University of Freiburg
Inputs
| ID | Name | Description | Type |
|---|---|---|---|
| body_fat_test | #main/body_fat_test | n/a |
|
| body_fat_test_labels | #main/body_fat_test_labels | n/a |
|
| body_fat_train | #main/body_fat_train | n/a |
|
Steps
| ID | Name | Description |
|---|---|---|
| 3 | Ensemble methods | toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_ensemble/sklearn_ensemble/1.0.8.1 |
| 4 | Ensemble methods | toolshed.g2.bx.psu.edu/repos/bgruening/sklearn_ensemble/sklearn_ensemble/1.0.8.1 |
| 5 | Plot actual vs predicted curves and residual plots | toolshed.g2.bx.psu.edu/repos/bgruening/plotly_regression_performance_plots/plotly_regression_performance_plots/0.1 |
Outputs
| ID | Name | Description | Type |
|---|---|---|---|
| _anonymous_output_4 | #main/_anonymous_output_4 | n/a |
|
| output_actual_vs_pred | #main/output_actual_vs_pred | n/a |
|
| output_residual_plot | #main/output_residual_plot | n/a |
|
| output_scatter_plot | #main/output_scatter_plot | n/a |
|
Version History
master
Creators and Submitter
Views: 53 Downloads: 6 Runs: 0
Created: 2nd Jun 2025 at 11:00
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