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---
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.
: Mean values for each of the properties for each of the iris species.
|Species |Sepal.Length|Sepal.Width|Petal.Length|Petal.Width|
|----------|------------|-----------|------------|-----------|
|setosa |5.006 |3.428 |1.462 |0.246 |
|versicolor|5.936 |2.770 |4.260 |1.326 |
|virginica |6.588 |2.974 |5.552 |2.026 |
```{.R}
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)
```
{#figure}
## Species prediction
``` R
library(MASS)
m <- lda(Species ~ Sepal.Width + Sepal.Length, data = iris)
p <- predict(m)
predicted_species <- p$class
table(predicted_species, iris$Species)
##
## predicted_species setosa versicolor virginica
## setosa 49 0 0
## versicolor 1 36 15
## virginica 0 14 35
```
This model predicts in 80% of the cases the correct species. However,
this is mainly for *setosa* for the other species the model predicts the
correct species only for 71% of the records.
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