Hyperactive
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SimonBlanke
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
To separate the discussion about the optimization-strategy api for v5 started in https://github.com/SimonBlanke/Hyperactive/pull/101. In the future it makes sense to rename this feature to something like "CompositeOptimizer" or "OptimizerPipeline". In...
Random discovery today, one of the `sktime` core developers - @jdb78, the author of `pytorch-forecasting` - has also written a gradient-free optimization package 5 years ago: https://github.com/jdb78/lipo Given the similarity...
A new data module instance is created for each optimization trial. Fixes #212
## Summary This PR adds integration for **sktime time series regression**, addressing . It introduces **TSROptCV**, enabling users to optimize sktime regressors using any Hyperactive optimizer (e.g., Random Search, Hill...
## Summary This PR adds a full integration with **skforecast**, allowing Hyperactive to optimize hyperparameters of skforecast forecasting models using any of its optimization algorithms. ## Implementation Details ### SkforecastExperiment...
### Summary Extend `ForecastingOptCV` to expose sktime’s broadcasting controls plus richer post-fit diagnostics, aligning it more closely with `ForecastingGridSearchCV` while keeping Hyperactive optimizers in play. Also document the new knobs...
- Adds an integration for tuning sktime detector / anomaly-detection estimators from Hyperactive. - Provides an experiment adapter `SktimeDetectorExperiment` and a wrapper estimator `TSDetectorOptCv` so Hyperactive optimizers can tune sktime...
It would be nice to have an estimator level integration with time series regressors in the `sktime` package. https://github.com/sktime/sktime This would require: * a `BaseExperiment` descendant class `SktimeRegressionExperiment` which carries...
This PR adds a `SktimeForecastingTask`, which defines a full benchmarking run for a `forecaster` that is passed later in `_evaluate`. This object could be used as a "task" in the...
The `TorchExperiment` reuses the same `LightningDataModule` instance across all optimization trials. If the datamodule maintains internal state (e.g., data augmentation settings, random state, preprocessing cache), this state persists across trials....
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An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.