Rejection Sampling is a method used in sambias costing function. It is sampling scheme that allows us to draw examples independently from a distribution X, given examples drawn independently from distribution Y.
a data frame containing the observations rowwise, along with their corresponding categorical strata feature
a numerical vector whose length must coincide with the number of the rows of data. The i-th value contains the inverse-probability e.g. determines how often the i-th observation of data shall be replicated.
Norbert Krautenbacher, Kevin Strauss, Maximilian Mandl, Christiane Fuchs
Krautenbacher, N., Theis, F. J., & Fuchs, C. (2017). Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies. Computational and mathematical methods in medicine, 2017.
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library(smotefamily) library(sambia) data.example <- sample_generator(100,ratio = 0.80) result <- gsub('n','0',data.example[,'result']) result <- gsub('p','1',result) data.example[,'result'] <- as.numeric(result) weights <- data.example[,'result'] weights <- ifelse(weights==1,1,4) rej.sample <- sambia:::rejSamp(data=data.example, weights = weights)
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