BDMLtools
Depended on by
Depends On
Depends On
Depends On
Depends On
Depends On
Depends On
Depends On
Depends On
- numpy (
numpy>=1.20) - lofo-importance (
lofo-importance>=0.3.1) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8.0) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - catboost (
catboost>=1.0.4) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - probatus (
probatus>=1.8.8) - mlxtend (
mlxtend>=0.19.0) - scikit-optimize (
scikit-optimize>=0.9.0) - shap (
shap>=0.38.1)
Depends On
- numpy (
numpy>=1.20) - lofo-importance (
lofo-importance>=0.3.1) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8.0) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - catboost (
catboost>=1.0.4) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - probatus (
probatus>=1.8.8) - mlxtend (
mlxtend>=0.19.0) - scikit-optimize (
scikit-optimize>=0.9.0) - shap (
shap>=0.38.1)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8.0) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8.0) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8.0) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8.0) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - plotnine (
plotnine>=0.8) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)
Depends On
- numpy (
numpy>=1.20) - fastparquet (
fastparquet>=0.7.1) - pandas (
pandas>=1.3.3) - statsmodels (
statsmodels>=0.13.0) - matplotlib (
matplotlib>=3.2.2) - scikit-learn (
scikit-learn>=1.0) - xgboost (
xgboost>=1.4.2) - scipy (
scipy>=1.5.0) - category_encoders (
category_encoders>=2.3.0) - lightgbm (
lightgbm>=3.3.0) - toad (
toad>=0.1.0) - patsy (
patsy>=0.5.2) - bayesian-optimization (
bayesian-optimization>=1.2.0) - shap (
shap>=0.40.0)