claesenm / optunity
optimization routines for hyperparameter tuning
☆419Updated last year
Alternatives and similar repositories for optunity:
Users that are interested in optunity are comparing it to the libraries listed below
- Bayesian Optimization using xgboost and sklearn API☆226Updated 9 years ago
- Tuning hyperparams fast with Hyperband☆593Updated 6 years ago
- A library for factorization machines and polynomial networks for classification and regression in Python.☆245Updated 4 years ago
- scikit-learn compatible projects☆410Updated last month
- Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models☆490Updated 7 years ago
- Python package for Bayesian Machine Learning with scikit-learn API☆517Updated 3 years ago
- Use evolutionary algorithms instead of gridsearch in scikit-learn☆773Updated last year
- Confidence intervals for scikit-learn forest algorithms☆288Updated 2 weeks ago
- A garden for scikit-learn compatible trees☆287Updated 10 months ago
- A Python implementation of Jerome Friedman's Multivariate Adaptive Regression Splines☆459Updated last year
- RoBO: a Robust Bayesian Optimization framework☆485Updated 6 years ago
- Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one…☆381Updated 3 years ago
- Compiled Decision Trees for scikit-learn☆224Updated 2 weeks ago
- HPOlib is a hyperparameter optimization library. It provides a common interface to three state of the art hyperparameter optimization pac…☆166Updated 6 years ago
- A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.☆418Updated 2 years ago
- Hyper-parameter optimization for sklearn☆1,622Updated 3 weeks ago
- Bayesian optimization for Python☆245Updated 3 years ago
- dask-searchcv is now part of dask-ml: https://github.com/dask/dask-ml☆240Updated 6 years ago
- Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimizati…☆1,396Updated 7 years ago
- Python code for bayesian optimization using Gaussian processes☆313Updated 8 years ago
- XGBoost Feature Interactions & Importance☆500Updated 7 years ago
- ML-Ensemble – high performance ensemble learning☆855Updated last year
- Library for machine learning stacking generalization.☆117Updated 6 years ago
- A deep learning tool for time series classification and regression☆364Updated 8 months ago
- Simple structured learning framework for python☆666Updated 3 years ago
- XGBoost Feature Interactions Reshaped☆429Updated 7 years ago
- Exploring differentiation with respect to hyperparameters☆295Updated 9 years ago
- InfiniteBoost: building infinite ensembles with gradient descent☆184Updated 6 years ago
- Bayesian Optimization using GPflow☆272Updated 4 years ago
- A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.☆212Updated 7 years ago