QSAR#66
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Abdelrahman-Mohamed-Taha-MAHMOUD wants to merge 1 commit intochiral-data:workflow-005-val-loss-issuefrom
Open
QSAR#66Abdelrahman-Mohamed-Taha-MAHMOUD wants to merge 1 commit intochiral-data:workflow-005-val-loss-issuefrom
Abdelrahman-Mohamed-Taha-MAHMOUD wants to merge 1 commit intochiral-data:workflow-005-val-loss-issuefrom
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Abdelrahman-Mohamed-Taha-MAHMOUD
February 5, 2026 00:04
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Pull request overview
This pull request implements a complete refactoring of the QSAR workflow, consolidating multiple nodes into a streamlined 4-stage pipeline with enhanced interactive dashboards and improved modularity.
Changes:
- Restructured workflow from 4 nodes to a new 4-node architecture with renamed directories (01-data-preparation → 1_data_prep, etc.)
- Removed the README documentation file
- Implemented comprehensive interactive HTML dashboards for each processing stage with Plotly visualizations
Reviewed changes
Copilot reviewed 43 out of 55 changed files in this pull request and generated 1 comment.
Show a summary per file
| File | Description |
|---|---|
| workflows/workflow-005/README.md | Complete removal of workflow documentation |
| workflows/workflow-005/.chiral/workflow.toml | Updated node dependencies to reflect new naming scheme |
| workflows/workflow-005/1_data_prep/* | New data preparation node with augmentation and feature selection |
| workflows/workflow-005/2_model_train/* | New model training node with hybrid architecture and regularization |
| workflows/workflow-005/3_analyze_overfitting/* | New overfitting analysis node with diagnostic visualizations |
| workflows/workflow-005/4_predict_from_csv/* | New CSV-based prediction node replacing web app approach |
| apps/q/qsar-hybrid-model/* | Docker configuration for the new pipeline architecture |
Comments suppressed due to low confidence (1)
workflows/workflow-005/2_model_train/3_model_train.py:1
- The selector description is misleading. The code doesn't use SelectKBest - it uses SelectFromModel with RandomForestRegressor as shown in 1_data_prep.py. This string should accurately reflect the actual feature selection method used.
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| [params.input_csv] | ||
| type = "string" | ||
| default = " " |
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The default value is a single space character rather than an empty string. This could cause unexpected behavior when checking if the parameter is empty. Consider using an empty string "" instead for clarity.
Suggested change
| default = " " | |
| default = "" |
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