#simulate a dataset with continuous data
dataset <- matrix(runif(400 * 50, 1, 50), ncol = 50 )
#the target feature is the last column of the dataset as a vector
y <- rbinom(400, 10, 0.6)
N <- runif(400, 11, 20)
target <- cbind(y/N, N)
results <- testIndBinom(target, dataset, xIndex = 24, csIndex = 10)
results
#run the SES algorithm using the testIndPois conditional independence test
a1 <- SES(target, dataset, max_k = 3, threshold = 0.05, test = "testIndBinom");
a2 <- MMPC(target, dataset, max_k = 3, threshold = 0.05, test = "testIndBinom");
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