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PrInDT  

Prediction and Interpretation in Decision Trees for Classification and Regression
View on CRAN: Click here


Download and install PrInDT package within the R console
Install from CRAN:
install.packages("PrInDT")

Install from Github:
library("remotes")
install_github("cran/PrInDT")

Install by package version:
library("remotes")
install_version("PrInDT", "1.0.1")



Attach the package and use:
library("PrInDT")
Maintained by
Claus Weihs
[Scholar Profile | Author Map]
First Published: 2023-04-12
Latest Update: 2023-05-09
Description:
Optimization of conditional inference trees from the package 'party' for classification and regression. For optimization, the model space is searched for the best tree on the full sample by means of repeated subsampling. Restrictions are allowed so that only trees are accepted which do not include pre-specified uninterpretable split results (cf. Weihs & Buschfeld, 2021a). The function PrInDT() represents the basic resampling loop for 2-class classification (cf. Weihs & Buschfeld, 2021a). The function RePrInDT() (repeated PrInDT()) allows for repeated applications of PrInDT() for different percentages of the observations of the large and the small classes (cf. Weihs & Buschfeld, 2021c). The function NesPrInDT() (nested PrInDT()) allows for an extra layer of subsampling for a specific factor variable (cf. Weihs & Buschfeld, 2021b). The functions PrInDTMulev() and PrInDTMulab() deal with multilevel and multilabel classification. In addition to these PrInDT() variants for classification, the function PrInDTreg() has been developed for regression problems. Finally, the function PostPrInDT() allows for a posterior analysis of the distribution of a specified variable in the terminal nodes of a given tree. References are: -- Weihs, C., Buschfeld, S. (2021a) "Combining Prediction and Interpretation in Decision Trees (PrInDT) - a Linguistic Example" ; -- Weihs, C., Buschfeld, S. (2021b) "NesPrInDT: Nested undersampling in PrInDT" ; -- Weihs, C., Buschfeld, S. (2021c) "Repeated undersampling in PrInDT (RePrInDT): Variation in undersampling and prediction, and ranking of predictors in ensembles" .
How to cite:
Claus Weihs (2023). PrInDT: Prediction and Interpretation in Decision Trees for Classification and Regression. R package version 1.0.1, https://cran.r-project.org/web/packages/PrInDT. Accessed 20 Feb. 2025.
Previous versions and publish date:
1.0 (2023-04-12 14:20)
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Complete documentation for PrInDT
Functions, R codes and Examples using the PrInDT R package
Full PrInDT package functions and examples
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