predict-idlab / powershapLinks
A power-full Shapley feature selection method.
☆208Updated last year
Alternatives and similar repositories for powershap
Users that are interested in powershap are comparing it to the libraries listed below
Sorting:
- All Relevant Feature Selection☆135Updated 2 months ago
- SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.☆150Updated 2 months ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆618Updated last year
- Random Forest or XGBoost? It is Time to Explore LCE☆66Updated last year
- Multiple Imputation with LightGBM in Python☆382Updated 10 months ago
- An extension of LightGBM to probabilistic modelling☆316Updated last year
- Calculates various features from time series data. Python implementation of the R package tsfeatures.☆412Updated last year
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆577Updated last year
- Flexible time series feature extraction & processing☆421Updated 9 months ago
- Hierarchical Time Series Forecasting with a familiar API☆224Updated 2 years ago
- Quantile Regression Forests compatible with scikit-learn.☆231Updated this week
- hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…☆64Updated 3 months ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆102Updated 2 years ago
- Forecasting with Gradient Boosted Time Series Decomposition☆195Updated last year
- Python package for Imputation Methods☆248Updated last year
- A python package for time series forecasting with scikit-learn estimators.☆161Updated last year
- Probabilistic Gradient Boosting Machines☆155Updated last year
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…☆651Updated 4 months ago
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆521Updated 2 months ago
- TimeSHAP explains Recurrent Neural Network predictions.☆176Updated last year
- Python implementation of binary and multi-class Venn-ABERS calibration☆163Updated 9 months ago
- Probabilistic prediction with XGBoost.☆110Updated 3 months ago
- Phi_K correlation analyzer library☆164Updated 4 months ago
- Python package for missing-data imputation with deep learning☆149Updated 9 months ago
- mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.☆599Updated 7 months ago
- For calculating global feature importance using Shapley values.☆271Updated last week
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆160Updated 2 years ago
- Fast SHAP value computation for interpreting tree-based models☆539Updated last year
- Bayesian time series forecasting and decision analysis☆115Updated 2 years ago
- A python library to build Model Trees with Linear Models at the leaves.☆373Updated 11 months ago