mob_fit_splitnode

weights

minsplit

objfun

verbose

<p>Utility Function. Taken from party package to remove ":::" warning</p>

Functions to implements random forest method for model based
recursive partitioning. The mob() function, developed by Zeileis et al. (2008),
within 'party' package, is modified to construct model-based decision trees based
on random forests methodology. The main input function mobforest.analysis() takes
all input parameters to construct trees, compute out-of-bag errors, predictions,
and overall accuracy of forest. The algorithm performs parallel computation
using cluster functions within 'parallel' package.

Kasey Jones

mobForest

Model Based Random Forest Analysis

mob_fit_splitnode function

Utility Function. Taken from party package to remove ":::" warning — mob_fit_splitnode

Utility Function. Taken from party package to remove ":::" warning

mob_fit_splitnode: Utility Function. Taken from party package to remove ":::" warning

Description

Usage

Arguments