The application uses the iris dataset. This famous (Fisher’s or Anderson’s) iris data set gives the measurements in centimeters of the variables sepal length and width and petal length and width, respectively, for 50 flowers from each of 3 species of iris. The species are Iris setosa, versicolor, and virginica.

A random forest classification algorithm is trained using the iris dataset with accuracy 1

set.seed(1000)
model <- train(Species~., 
               data = iris, 
               method = "rf", 
               preProcess = c("center", "scale"),
               tuneLength = 1,
               trControl = trainControl(method = "none", number = 1))

The user changes the input variables (sepal length and width, petal length and width in centimeters) using the sliders. The application predicts the species of the flower using the trained random forest model. The app is available here:
Prediction using Edgar Anderson’s Iris Data