tornede / py_experimenterLinks
The PyExperimenter is a tool for the automatic execution of experiments, e.g. for machine learning (ML), capturing corresponding results in a unified manner in a database.
☆38Updated 2 months ago
Alternatives and similar repositories for py_experimenter
Users that are interested in py_experimenter are comparing it to the libraries listed below
Sorting:
- Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.☆78Updated this week
- scikit-activeml: A Comprehensive and User-friendly Active Learning Library☆180Updated this week
- An interactive framework to visualize and analyze your AutoML process in real-time.☆92Updated last week
- Python Meta-Feature Extractor package.☆137Updated 3 months ago
- Repository for TabICL: A Tabular Foundation Model for In-Context Learning on Large Data☆245Updated last week
- A Living Benchmark for Machine Learning on Tabular Data☆152Updated this week
- Fast and incremental explanations for online machine learning models. Works best with the river framework.☆55Updated 11 months ago
- 👋 Puncc is a python library for predictive uncertainty quantification using conformal prediction.☆358Updated this week
- Python package for conformal prediction☆548Updated 2 months ago
- An automated machine learning tool aimed to facilitate AutoML research.☆102Updated last year
- Effector - a Python package for global and regional effect methods☆117Updated 4 months ago
- In-context Bayesian Optimization☆16Updated 3 weeks ago
- Competing Risks and Survival Analysis☆111Updated 2 months ago
- Conformalized Quantile Regression☆296Updated 3 years ago
- Repository for CARTE: Context-Aware Representation of Table Entries☆160Updated 3 months ago
- Quantile Regression Forests compatible with scikit-learn.☆250Updated 2 weeks ago
- Scikit-learn compatible decision trees beyond those offered in scikit-learn☆85Updated this week
- A build-it-yourself AutoML Framework☆72Updated last year
- A Library for Uncertainty Quantification.☆922Updated 7 months ago
- 👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster☆115Updated 2 months ago
- Shapley Interactions and Shapley Values for Machine Learning☆642Updated last week
- Classification metrics and post-hoc calibration☆45Updated 2 weeks ago
- xRFM: Accurate, scalable, and interpretable feature learning models for tabular data☆32Updated this week
- An extension of LightGBM to probabilistic modelling☆347Updated last week
- Our maintained PFN repository. Come here to train SOTA PFNs.☆121Updated 2 months ago
- scikit-learn contrib estimators☆198Updated 3 weeks ago
- Probabilistic prediction with XGBoost.☆120Updated 8 months ago
- For calculating global feature importance using Shapley values.☆280Updated last week
- ML models + benchmark for tabular data classification and regression☆297Updated last month
- [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets☆88Updated 2 years ago