smazzanti / tds_black_box_models_more_explainable
Jupyter Notebook used for writing the article "Black-Box models are actually more explainable than a Logistic Regression" published in Towards Data Science: https://towardsdatascience.com/black-box-models-are-actually-more-explainable-than-a-logistic-regression-f263c22795d
☆73Updated 2 years ago
Alternatives and similar repositories for tds_black_box_models_more_explainable:
Users that are interested in tds_black_box_models_more_explainable are comparing it to the libraries listed below
- How to Interpret SHAP Analyses: A Non-Technical Guide☆52Updated 3 years ago
- xverse (XuniVerse) is collection of transformers for feature engineering and feature selection☆117Updated last year
- (ml) - python implementation of bayesian media mix modelling with shape and carryover effect☆58Updated 3 years ago
- Python implementation of the population stability index (PSI)☆139Updated last year
- Python package that optimizes information value, weight-of-evidence monotonicity and representativeness of features for credit scorecard …☆117Updated 2 years ago
- Categorical Embedder is a python package that let's you convert your categorical variables into numeric via Neural Networks☆25Updated 5 years ago
- Tips for Advanced Feature Engineering☆52Updated 4 years ago
- Repository for the research and implementation of categorical encoding into a Featuretools-compatible Python library☆51Updated 2 years ago
- A full example for causal inference on real-world retail data, for elasticity estimation☆50Updated 3 years ago
- ☆136Updated 6 years ago
- Using Imblearn To Tackle Imbalanced Data Sets☆37Updated 8 years ago
- Example usage of scikit-hts☆57Updated 2 years ago
- scikit-learn compatible tools for building credit risk acceptance models☆99Updated 2 months ago
- Public solution for AutoSeries competition☆72Updated 5 years ago
- zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range fr…☆244Updated 4 months ago
- Random Forest or XGBoost? It is Time to Explore LCE☆66Updated last year
- Kaggle Days Paris - Competitive GBDT Specification and Optimization Workshop☆92Updated 2 years ago
- A python package for feature selection in python☆51Updated 4 years ago
- A re-creation of SAS varclus procedure in Python☆23Updated 6 years ago
- Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.☆51Updated last year
- Implementation of feature engineering from Feature engineering strategies for credit card fraud☆41Updated 4 years ago
- Nested cross-validation for unbiased predictions. Can be used with Scikit-Learn, XGBoost, Keras and LightGBM, or any other estimator that…☆64Updated 5 years ago
- Quick Implementation in python☆52Updated 5 years ago
- Python package for Gower distance☆77Updated 11 months ago
- scikit-learn compatible implementation of stability selection.☆212Updated last year
- ☆286Updated last year
- ☆51Updated 6 years ago
- A presention of core concepts and a data generator making easier using tabular data with TensorFlow and Keras☆44Updated 2 years ago
- An implementation of the minimum description length principal expert binning algorithm by Usama Fayyad☆105Updated last year
- Hierarchical Time Series Forecasting with a familiar API☆224Updated last year