cerlymarco / shap-hypetuneLinks
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
☆581Updated last year
Alternatives and similar repositories for shap-hypetune
Users that are interested in shap-hypetune are comparing it to the libraries listed below
Sorting:
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…☆674Updated 9 months ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆638Updated last year
- Fast SHAP value computation for interpreting tree-based models☆546Updated 2 years ago
- Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…☆764Updated last year
- SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.☆155Updated 7 months ago
- A power-full Shapley feature selection method.☆211Updated last month
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆532Updated 8 months ago
- Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upo…☆544Updated 10 months ago
- Multiple Imputation with LightGBM in Python☆396Updated last month
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.☆617Updated last year
- The practitioner's forecasting library☆346Updated last month
- A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.☆469Updated 2 years ago
- Leave One Feature Out Importance☆853Updated 9 months ago
- Flexible time series feature extraction & processing☆436Updated last year
- A python library to build Model Trees with Linear Models at the leaves.☆387Updated last year
- EvalML is an AutoML library written in python.☆833Updated 2 weeks ago
- Python package for Imputation Methods☆251Updated last year
- Calculates various features from time series data. Python implementation of the R package tsfeatures.☆435Updated last year
- All Relevant Feature Selection☆142Updated 7 months ago
- An extension of XGBoost to probabilistic modelling☆670Updated last week
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,491Updated last week
- An extension of LightGBM to probabilistic modelling☆345Updated this week
- Forecasting with Gradient Boosted Time Series Decomposition☆197Updated 2 years ago
- distfit is a python library for probability density fitting.☆407Updated 3 weeks ago
- XGBoost + Optuna☆725Updated last year
- A python package for time series forecasting with scikit-learn estimators.☆162Updated last year
- Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…☆501Updated last month
- Improving XGBoost survival analysis with embeddings and debiased estimators☆342Updated last year
- Synthetic Minority Over-Sampling Technique for Regression☆348Updated last year
- Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.☆716Updated this week