| Filename | Description | Uploaded At | Storage | Operation |
|---|---|---|---|---|
| optimum features_ensemble.png | Optimum features producing max accuracy for the ensemble! | 2025-08-26 16:20:35 | Drive | View | Download |
| Class Distribution of model data.png | Distribution of the parsed & curated compounds according to their oxidation state. | 2025-08-26 16:20:34 | Drive | View | Download |
| Weighted base models vs performance.png | The base models (custom, final), if weighted, how the performance would change. | 2025-08-26 16:20:33 | Drive | View | Download |
| Weighted base models vs performance without LGBM.png | The base models (as in the paper this project reflected) , if weighted, how the performance would change | 2025-08-26 16:20:32 | Drive | View | Download |
| optimum features_extra_trees.png | Optimum features producing max accuracy for one of the base models (ExtrTreesClassifier)) | 2025-08-26 16:20:31 | Drive | View | Download |
| Learning curve for GB base model.png | To tune the base models hyperopt was used. A learning curve helps to estimate how many trials an algorithm (GradientBoosting) might need for choosing the right hyperparameters. | 2025-08-26 16:20:30 | Drive | View | Download |
| confusion matrix_paper.png | The confusion matrix of the ensemble (pretrained) as loaded from the authors shared space. | 2025-08-26 16:20:29 | Drive | View | Download |
| PCA_Cu.png | Principal component analysis for the cu complexes present in the dataset. | 2025-08-26 16:20:27 | Drive | View | Download |