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Generate the data from two simulation cases in Tian, Y., & Feng, Y. (2021).
generate_data(n = 1000, model.no = 1)
A list with two components x and y. x is the predictor matrix and y is the label vector.
the generated sample size. Default = 1000.
the model number in Tian, Y., & Feng, Y. (2021). Can be 1 or 2. Default = 1.
Tian, Y., & Feng, Y. (2021). Neyman-Pearson Multi-class Classification via Cost-sensitive Learning. Submitted. Available soon on arXiv.
npcs, predict.npcs, error_rate, and gamma_smote.
npcs
predict.npcs
error_rate
gamma_smote
set.seed(123, kind = "L'Ecuyer-CMRG") train.set <- generate_data(n = 1000, model.no = 1) x <- train.set$x y <- train.set$y
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