Hypergbm

Latest version: v0.3.2

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0.2.5.4

* Add compatibility with scikit-learn v1.1
* Fix TfidfPrimitive

0.2.5.3

* Support custom metric in experiment visualization
* Set experiment `cv` default to `False` if eval_data is not None
* Fix issues: 80, 82

0.2.5.2

* Fix experiment report in gpu mode

0.2.5.1

* Add compatibility with cuML 22.02

0.2.5

This version brings the following new features:

* Full pipeline GPU acceleration
* Data adaption
* Data cleaning
* Feature selection
* Data drift detection
* Feature selection(2nd stage)
* Pseudo labeling(2nd stage)
* Optimization
* Data preprocessing
* Model fitting
* Model ensemble
* Metrics
* Model training
* Add TargetEncoder for categories
* Set estimator eval_metric based on experiment reward_metric
* Advanced Features
* Data adaption in experiment
* Experiment Visualization
* Experiment configurations
* Dataset information
* Processing information
* Multijob management
* Series and parallel jobs scheduling
* Local and remote jobs execution
* Export experiment report

0.2.3.2

Upgrade requirements

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