install.packages(“caret”, repos = “http://cran.us.r-project.org”) library(caret)
names(getModelInfo())
set.seed(123)
x <- matrix(rnorm(50 * 5), ncol = 5) y <- factor(rep(c(“A”, “B”), 25))
featurePlot(x, y, plot = “box”) featurePlot(x, y, plot = “density”)
jpeg(“boxplot.jpg”) featurePlot(x, y, plot = “box”) dev.off()
jpeg(“density.jpg”) featurePlot(x, y, plot = “density”) dev.off()
install.packages(“FSelector”, repos = “http://cran.us.r-project.org”) library(FSelector)
install.packages(“FSelectorRcpp”) library(FSelectorRcpp)
gain <- information_gain(Species ~ ., iris) print(gain)
install.packages(“arules”, repos = “http://cran.us.r-project.org”) library(arules)
data(iris) iris_interval <- discretize(iris\(Sepal.Length, method = "interval", breaks = 5) iris_frequency <- discretize(iris\)Sepal.Length, method = “frequency”, breaks = 5) iris_cluster <- discretize(iris\(Sepal.Length, method = "cluster", breaks = 5) iris_fixed <- discretize(iris\)Sepal.Length, method = “fixed”, categories = c(“0-4”, “4-6”, “6-8”, “8-10”))
print(iris_interval) print(iris_frequency) print(iris_cluster) print(iris_fixed)
install.packages(“Boruta”, repos = “http://cran.us.r-project.org”) library(Boruta)
install.packages(“mlbench”, repos = “http://cran.us.r-project.org”) library(mlbench)
data(“Ozone”) set.seed(123) Ozone <- na.omit(Ozone)
boruta_result <- Boruta(V4 ~ ., data = Ozone, doTrace = 2) print(boruta_result)
selected_features <- getSelectedAttributes(boruta_result) Ozone_selected <- Ozone[, c(selected_features, “V4”)]
boxplot(Ozone_selected, main = “Selected Features Boxplot”)