CaseBasedReasoning: Case-Based Reasoning

Given a large set of problems and their individual solutions case based reasoning seeks to solve a new problem by referring to the solution of that problem which is "most similar" to the new problem. Crucial in case based reasoning is the decision which problem "most closely" matches a given new problem. The basic idea is to define a family of distance functions and to use these distance functions as parameters of local averaging regression estimates of the final result. Then that distance function is chosen for which the resulting estimate is optimal with respect to a certain error measure used in regression estimation. The idea is based on: Dippon J. et al. (2002) <doi:10.1016/S0167-9473(02)00058-0>.

Version: 0.1
Imports: R6, ranger, survival, tidyverse, cowplot, dplyr, data.table, magrittr, rms, Rcpp, RcppParallel
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: testthat, knitr, rmarkdown, RcppArmadillo
Published: 2018-06-12
Author: Dr. Simon Mueller, PD Dr. Juergen Dippon
Maintainer: Dr. Simon Mueller <simon.mueller at>
License: AGPL
NeedsCompilation: yes
SystemRequirements: C++11
Materials: README
CRAN checks: CaseBasedReasoning results


Reference manual: CaseBasedReasoning.pdf
Vignettes: Case Based Reasoning: Cox-Beta-Model
Case Based Reasoning: RandomForest-Model
Package source: CaseBasedReasoning_0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: CaseBasedReasoning_0.1.tgz, r-oldrel: not available


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