Sstack: Bootstrap Stacking of Random Forest Models for Heterogeneous Data

Generates and predicts a set of linearly stacked Random Forest models using bootstrap sampling. Individual datasets may be heterogeneous (not all samples have full sets of features). Contains support for parallelization but the user should register their cores before running. This is an extension of the method found in Matlock (2018) <doi:10.1186/s12859-018-2060-2>.

Getting started

Package details

AuthorKevin Matlock, Raziur Rahman
MaintainerKevin Matlock <>
Package repositoryView on CRAN
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Sstack documentation built on May 2, 2019, 5:39 a.m.