Man pages for acca3003/ngboostR
R Wrapper for NGBoost python module
| Bernoulli | Bernoulli Distribution (Categorical with k=1) |
| Cauchy | Cauchy Distribution |
| create_classifier | Create a NGBoostClassifier object |
| create_regressor | Create a NGBoostRegressor object |
| DecisionTreeRegressor | DecisionTreeRegressor |
| default_linear_learner | Default LinearTreeRegressor |
| default_tree_learner | Default DecisionTreeRegressor |
| Exponential | Exponential Distribution |
| fit_classifier | Train a NGBoostClassifier object |
| fit_regressor | Train a NGBoostRegressor object |
| install_ngboost | Installation Python ngboost module |
| k_categorical | Categorical Distribution |
| Laplace | Laplace Distribution |
| LogNormal | LogNormal Distribution |
| MultivariateNormal | Multivariante Normal Distribution |
| ngboost | NGBoost for R |
| ngboost_python_version | Version Number of the python module NGBoost |
| Normal | Normal Distribution |
| Poisson | Poisson Distribution |
| predict_classifier | Predict using a NGBoostClassifier object |
| predict_classifier_dist | Predict Distribution (Bernoulli o Cateogiral) using... |
| predict_classifier_prob | Predict using a NGBoostClassifier object as a probability |
| predict_regressor | Predict using a NGBoostRegressor object |
| predict_regressor_dist | Predict Normal distribution using NGBoostRegressor object |
| Ridge | LinearTreeRegressor |
| T | Student T Distribution |
