mboost v0.4-11

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by Torsten Hothorn

Model-Based Boosting

Functional gradient descent algorithms (boosting) for optimizing general loss functions utilizing componentwise least squares, either of parametric linear form or smoothing splines, or regression trees as base learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

Functions in mboost

Name Description
IPCweights Inverse Probability of Censoring Weights
cvrisk Cross-Validation
blackboost Gradient Boosting with Regression Trees
bodyfat Prediction of Body Fat by Skinfold Thickness, Circumferences, and Bone Breadths
Family Gradient Boosting Families
boost_family-class Class "boost_family": Gradient Boosting Family
methods Methods for Gradient Boosting Objects
gamboost Gradient Boosting with Componentwise Smoothing Splines
FP Fractional Polynomials
boost_dpp Data Preprocessing for Gradient Boosting
boost_control Control Hyper Parameters for Boosting Algorithms
glmboost Gradient Boosting with Componentwise Linear Models
wpbc Wisconsin Prognostic Breast Cancer Data
westbc Breast Cancer Gene Expression
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Details

Date $Date: 2006/08/31 15:06:54 $
SaveImage yes
License GPL
Packaged Thu Sep 7 13:30:35 2006; hothorn

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