C2SPrInDT |
Two-stage estimation for classification |
data_land |
Landscape analysis |
data_speaker |
Subject pronouns and a predictor with one very frequent level |
data_vowel |
Vowel length |
data_zero |
Subject pronouns |
Mix2SPrInDT |
Two-stage estimation for classification-regression mixtures |
NesPrInDT |
Nested 'PrInDT' with additional undersampling of a factor with two unbalanced levels |
OptPrInDT |
Optimisation of undersampling percentages for classification |
participant_zero |
Participants of subject pronoun study |
PostPrInDT |
Posterior analysis of conditional inference trees: distribution of a specified variable in the terminal nodes. |
PrInDT |
The basic undersampling loop for classification |
PrInDTAll |
Conditional inference tree (ctree) based on all observations |
PrInDTAllparts |
Conditional inference trees (ctrees) based on consecutive parts of the full sample |
PrInDTCstruc |
Structured subsampling for classification |
PrInDTMulab |
Multiple label classification based on resampling by 'PrInDT' |
PrInDTMulabAll |
Multiple label classification based on all observations |
PrInDTMulev |
PrInDT analysis for a classification problem with multiple classes. |
PrInDTMulevAll |
Conditional inference tree (ctree) for multiple classes on all observations |
PrInDTreg |
Regression tree resampling by the PrInDT method |
PrInDTregAll |
Regression tree based on all observations |
PrInDTRstruc |
Structured subsampling for regression |
R2SPrInDT |
Two-stage estimation for regression |
RePrInDT |
Repeated 'PrInDT' for specified percentage combinations |
SimCPrInDT |
Interdependent estimation for classification |
SimMixPrInDT |
Interdependent estimation for classification-regression mixtures |
SimRPrInDT |
Interdependent estimation for regression |