#require(nnet)
#require(ordinal)
#simulate a dataset with categorical data
dataset_m <- matrix( sample(c(0, 1, 2), 50 * 100, replace = TRUE), ncol = 50)
#initialize categorical target
target_m <- dataset_m[, 50]
#remove target from the dataset
dataset_m <- dataset_m[, -50]
#run the conditional independence test for the nominal class variable
results_m <- testIndLogistic(target_m, dataset_m, xIndex = 44, csIndex = c(10, 20),
target_type = 2)
results_m
#run the SES algorithm using the testIndLogistic conditional independence test
#for the nominal class variable
sesObject <- SES(as.factor(target_m), dataset_m, max_k = 3, threshold = 0.05,
test = "testIndLogistic");
#print summary of the SES output
summary(sesObject);
# plot the SES output
# plot(sesObject, mode = "all");
########################################################################
#run the conditional independence test for the ordinal class variable
results_o <- testIndLogistic(target_m, dataset_m, xIndex = 44, csIndex = c(10, 20),
target_type = 3)
results_o
#run the SES algorithm using the testIndLogistic conditional independence test
#for the ordinal class variable
sesObject <- SES(factor(target_m, ordered=TRUE), dataset_m, max_k = 3 ,
threshold = 0.05, test = "testIndLogistic");
#print summary of the SES output
summary(sesObject);
# plot the SES output
# plot(sesObject, mode = "all");
########################################################################
#simulate a dataset with binary data
dataset_b <- matrix(sample(c(0,1),50 * 60, replace = TRUE), ncol = 50)
#initialize binary target
target_b <- dataset_b[, 50]
#remove target from the dataset
dataset_b <- dataset_b[, -50]
#run the conditional independence test for the binary class variable
results_b <- testIndLogistic(target_b, dataset_b, xIndex = 44, csIndex = c(10, 20),
target_type = 1)
results_b
#run the SES algorithm using the testIndLogistic conditional independence test
#for the binary class variable
sesObject <- SES(target_b, dataset_b, max_k = 3, threshold = 0.05,
test = "testIndLogistic");
#print summary of the SES output
summary(sesObject);
# plot the SES output
# plot(sesObject, mode = "all");
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