Prediction algorithms, hyperparameterization, evaluation

[glitt13]

These updates add hyperparameter grid search, prediction, evaluation, algorithm saving, and metadata writing capabilities for formulation metrics/hydrologic signatures based on catchment attributes at user-defined locations.

Additions

• Expanded the AlgoTrainEval class, with the train_eval() function performing the core processing steps, consisting of the following:

1. train-test split (not part of this commit)
2. hyperparameter grid search for optimized algorithms (this commit)
3. train algorithms (not part of this commit)
4. make predictions (part of this commit)
5. evaluate predictions (part of this commit)
6. save algorithms (part of this commit)
7. save metadata from the model training/prediction (part of this commit)

Removals

Changes

Testing

Screenshots

Notes

Todos

Checklist

• PR has an informative and human-readable title
• Changes are limited to a single goal (no scope creep)
• Code can be automatically merged (no conflicts)
• Code follows project standards (link if applicable)
• Passes all existing automated tests
• Any change in functionality is tested
• New functions are documented (with a description, list of inputs, and expected output)
• Placeholder code is flagged / future todos are captured in comments
• Visually tested in supported browsers and devices (see checklist below 👇)
• Project documentation has been updated (including the "Unreleased" section of the CHANGELOG)
• Reviewers requested with the Reviewers tool ➡️

Testing checklist

Target Environment support

• Windows
• Linux
• Browser

Accessibility

• Keyboard friendly
• Screen reader friendly

Other

• Is useable without CSS
• Is useable without JS
• Flexible from small to large screens
• No linting errors or warnings
• JavaScript tests are passing