mboost v2.4-1

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by Torsten Hothorn

Model-Based Boosting

Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

Functions in mboost

Name Description
FP Fractional Polynomials
mboost-package mboost: Model-Based Boosting
Family Gradient Boosting Families
boost_family-class Class "boost_family": Gradient Boosting Family
glmboost Gradient Boosting with Component-wise Linear Models
methods Methods for Gradient Boosting Objects
confint.mboost Pointwise Bootstrap Confidence Intervals
mboost Model-based Gradient Boosting
baselearners Base-learners for Gradient Boosting
IPCweights Inverse Probability of Censoring Weights
stabsel Stability Selection
cvrisk Cross-Validation
blackboost Gradient Boosting with Regression Trees
gamboost Gradient Boosting with Smooth Components
survFit Survival Curves for a Cox Proportional Hazards Model
boost_control Control Hyper-parameters for Boosting Algorithms
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