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mboost (version 0.4-6)

Gradient Boosting for Fitting Generalized Linear, Additive and Interaction Models

Description

Functional gradient descent algorithms for optimizing arbitrary loss functions utilizing componentwise least squares, either linear models or smoothing splines, and regression trees as base learners.

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Version

Install

install.packages('mboost')

Monthly Downloads

3,661

Version

0.4-6

License

GPL

Maintainer

Torsten Hothorn

Last Published

August 22nd, 2024

Functions in mboost (0.4-6)

methods

Methods for Gradient Boosting Objects

boost_family-class

Class "boost_family": Gradient Boosting Family

boost_dpp

Data Preprocessing for Gradient Boosting

blackboost

Gradient Boosting with Regression Trees

westbc

Breast Cancer Gene Expression

bodyfat

Prediction of Body Fat by Skinfold Thickness, Circumferences, and Bone Breadths

wpbc

Wisconsin Prognostic Breast Cancer Data

glmboost

Gradient Boosting with Componentwise Linear Models

Family

Gradient Boosting Families

IPCweights

Inverse Probability of Censoring Weights

gamboost

Gradient Boosting with Componentwise Smoothing Splines

boost_control

Control Hyper Parameters for Boosting Algorithms

Fractional Polynomials