Man pages for schalkdaniel/compboost
Efficient Component-Wise Boosting Implementation
| BaselearnerCategoricalBinary | Base learner to encode one single class of a categorical... |
| BaselearnerCategoricalRidge | One-hot encoded base learner for a categorical feature |
| BaselearnerCentered | Centering a base learner by another one |
| BaselearnerCustom | Custom base learner using 'R' functions. |
| BaselearnerPolynomial | Polynomial base learner |
| BaselearnerPSpline | Non-parametric B or P-spline base learner |
| BaselearnerTensor | Row-wise tensor product base learner |
| BlearnerFactoryList | Base learner factory list to define the set of base learners |
| boostComponents | Wrapper to boost general additive models using components |
| boostLinear | Wrapper to boost linear models for each feature. |
| boostSplines | Wrapper to boost general additive models for each feature. |
| CategoricalDataRaw | Data class for categorical variables |
| Compboost | Component-wise boosting |
| Compboost_internal | Internal Compboost Class |
| getCustomCppExample | Get C++ example script to define a custom cpp logger |
| InMemoryData | Store data in RAM |
| LearnerClassifCompboost | Component-wise gradient boosting classification learner |
| LearnerCompboost | Component-wise gradient boosting learner |
| LearnerRegrCompboost | Component-wise gradient boosting regression learner |
| LoggerInbagRisk | Log the train risk. |
| LoggerIteration | Logger class to log the current iteration |
| LoggerList | Collect loggers |
| LoggerOobRisk | Log the validation/test/out-of-bag risk |
| LoggerTime | Log the runtime |
| LossAbsolute | Absolute loss for regression tasks. |
| LossBinomial | 0-1 Loss for binary classification derived of the binomial... |
| LossCustom | Create LossCustom by using R functions. |
| LossHuber | Huber loss for regression tasks. |
| LossQuadratic | Quadratic loss for regression tasks. |
| LossQuantile | Quantile loss for regression tasks. |
| OptimizerAGBM | Nesterovs momentum |
| OptimizerCoordinateDescent | Coordinate descent |
| OptimizerCoordinateDescentLineSearch | Coordinate descent with line search |
| OptimizerCosineAnnealing | Coordinate descent with cosine annealing |
| plotBaselearner | Visualize contribution of one base learner |
| plotBaselearnerTraces | Visualize base learner traces |
| plotFeatureImportance | Visualize the feature importance |
| plotIndividualContribution | Decompose the predicted value based on the given features |
| plotPEUni | Visualize partial effect of a feature |
| plotRisk | Visualize the risk |
| plotTensor | Visualize bivariate tensor products |
| ResponseBinaryClassif | Create response object for binary classification. |
| ResponseRegr | Create response object for regression. |
