stanfordmlgroup / ngboostLinks
Natural Gradient Boosting for Probabilistic Prediction
☆1,756Updated 3 weeks ago
Alternatives and similar repositories for ngboost
Users that are interested in ngboost are comparing it to the libraries listed below
Sorting:
- Python implementations of the Boruta all-relevant feature selection method.☆1,578Updated 10 months ago
- python partial dependence plot toolbox☆860Updated 10 months ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆618Updated last year
- An extension of XGBoost to probabilistic modelling☆627Updated 2 months ago
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆1,982Updated last month
- Hyper-parameter optimization for sklearn☆1,635Updated 2 months ago
- A library of sklearn compatible categorical variable encoders☆2,450Updated 3 weeks ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,478Updated last week
- PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf☆2,799Updated 8 months ago
- ML-Ensemble – high performance ensemble learning☆858Updated last year
- Feature engineering package with sklearn like functionality☆2,089Updated this week
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆520Updated 3 months ago
- [HELP REQUESTED] Generalized Additive Models in Python☆897Updated last year
- Sequential model-based optimization with a `scipy.optimize` interface☆2,781Updated last year
- A standard framework for modelling Deep Learning Models for tabular data☆1,548Updated this week
- machine learning with logical rules in Python☆641Updated last year
- A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima…☆1,654Updated 7 months ago
- Leave One Feature Out Importance☆835Updated 4 months ago
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆578Updated last year
- Extra blocks for scikit-learn pipelines.☆1,347Updated 2 weeks ago
- Combining tree-boosting with Gaussian process and mixed effects models☆619Updated this week
- Python implementation of the rulefit algorithm☆421Updated last year
- Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data☆490Updated 4 years ago
- A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.☆467Updated last year
- Python package for stacking (machine learning technique)☆692Updated 10 months ago
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,435Updated this week
- Algorithms for explaining machine learning models☆2,532Updated 3 weeks ago
- A Python library for dynamic classifier and ensemble selection☆489Updated last year
- Code to compute permutation and drop-column importances in Python scikit-learn models☆618Updated 3 months ago
- Multiple Imputation with LightGBM in Python☆384Updated 11 months ago