Learn R Programming
⚠️There's a newer version (2.9-11) of this package.Take me there.

mboost (version 2.2-3)

Model-Based Boosting

Description

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.

Copy Link

Version

Install

install.packages('mboost')

Monthly Downloads

3,971

Version

2.2-3

License

GPL-2

Maintainer

Torsten Hothorn

Last Published

September 9th, 2013

Functions in mboost (2.2-3)

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