inst/examples/iris.md

In djvanderlaan/tinymarkdown: Simple Engine for Generating Reports using R

title: An analysis of iris

Introduction

From the help page of the iris data set:

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.

Descriptives

The table below shows for each of the iris species the mean value of the colums in the data set.

```{.R #table fun=output_table caption="Mean values for each of the properties for each of the iris species."} aggregate(iris[1:4], iris["Species"], mean)

```{.R #figure fun=output_figure 
  caption="Relation between sepal length and width for the different iris species." 
  name="iris" height=6 width=8 units="in" res=150 echo=TRUE}
pal <- hcl.colors(3, "Dark2")
plot(iris$Sepal.Width, iris$Sepal.Length, pch = 20, 
  col = pal[iris$Species], xlab = "Sepal Width", 
  ylab = "Sepal Length", bty = 'n', las = 1)
legend("topright", legend = levels(iris$Species), 
  fill = pal, bty = 'n', border = NA)

Species prediction

library(MASS)
m <- lda(Species ~ Sepal.Width + Sepal.Length, data = iris)
p <- predict(m)
predicted_species <- p$class
table(predicted_species, iris$Species)

This model predicts in round(mean(predicted_species==iris$Species)*100){.R}% of the cases the correct species. However, this is mainly for setosa for the other species the model predicts the correct species only for sel<-iris$Species!="setosa";round(100*mean(predicted_species[sel] == iris$Species[sel])){.R}% of the records.

djvanderlaan/tinymarkdown documentation built on March 19, 2023, 11:56 p.m.