Regression GradientBoosting
6.0

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Workflow Type: Galaxy

Machine learning: classification and regression

Associated Tutorial

This workflows is part of the tutorial Regression GradientBoosting, available in the GTN

Features

Includes Galaxy Workflow Tests

Thanks to...

Tutorial Author(s): Anup Kumar, Bérénice Batut

SEEK ID: https://dev.workflowhub.eu/workflows/1288?version=1

Inputs

ID	Name	Description	Type
body_fat_test	#main/body_fat_test	n/a	File
body_fat_test_labels	#main/body_fat_test_labels	n/a	File
body_fat_train	#main/body_fat_train	n/a	File

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	File
output_actual_vs_pred	#main/output_actual_vs_pred	n/a	File
output_residual_plot	#main/output_residual_plot	n/a	File
output_scatter_plot	#main/output_scatter_plot	n/a	File

Version History

6.0 (earliest) Created 25th Jun 2024 at 11:20 by Helena Rasche

Added/updated 4 files

Open master 90aabf2

Creators and Submitter

Creators

Not specified

Submitter

Helena Rasche

Discussion Channel

GTN Matrix

Tool

scikit-learn

License

Creative Commons Attribution 4.0 International

Activity

Views: 319 Downloads: 97

Created: 25th Jun 2024 at 11:19

Last updated: 25th Jun 2024 at 11:20

Regression GradientBoosting 6.0