mboost v2.2-3

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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
Family Gradient Boosting Families
FP Fractional Polynomials
cvrisk Cross-Validation
blackboost Gradient Boosting with Regression Trees
boost_family-class Class "boost_family": Gradient Boosting Family
boost_control Control Hyper-parameters for Boosting Algorithms
survFit Survival Curves for a Cox Proportional Hazards Model
wpbc Wisconsin Prognostic Breast Cancer Data
bodyfat Prediction of Body Fat by Skinfold Thickness, Circumferences, and Bone Breadths
gamboost Gradient Boosting with Smooth Components
mboost Model-based Gradient Boosting
mboost-package mboost: Model-Based Boosting
birds Habitat Suitability for Breeding Bird Communities
Westbc Breast Cancer Gene Expression
methods Methods for Gradient Boosting Objects
baselearners Base-learners for Gradient Boosting
glmboost Gradient Boosting with Component-wise Linear Models
stabsel Stability Selection
IPCweights Inverse Probability of Censoring Weights
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Details

Date 2013-09-09
LazyData yes
License GPL-2
URL http://r-forge.r-project.org/projects/mboost/
Packaged 2013-09-09 09:29:51 UTC; bhofner
NeedsCompilation yes
Repository CRAN
Date/Publication 2013-09-09 14:36:44

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