reconstructGBMdata

a <code><a rd-options="" href="/link/gbm.object?package=gbm&version=2.1.4" data-mini-rdoc="gbm::gbm.object">gbm.object</a></code> initially fit using <code><a rd-options="" href="/link/gbm?package=gbm&version=2.1.4" data-mini-rdoc="gbm::gbm">gbm</a></code>

Helper function to reconstitute the data for plots and summaries. This
function is not intended for the user to call directly.

manip

An implementation of extensions to Freund and Schapire's AdaBoost
algorithm and Friedman's gradient boosting machine. Includes regression
methods for least squares, absolute loss, t-distribution loss, quantile
regression, logistic, multinomial logistic, Poisson, Cox proportional hazards
partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and
Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway.

Brandon Greenwell

Generalized Boosted Regression Models

Bradley Boehmke

Jay Cunningham

GBM Developers

reconstructGBMdata function

a <code><a rd-options='' href='gbm.object'>gbm.object</a></code> initially fit using <code><a rd-options='' href='gbm'>gbm</a></code>

reconstructGBMdata: Reconstruct a GBM's Source Data

Description

Usage

Arguments

Value

See Also