let us have look at slightly more complex iris dataset we will use it later to contrast lda with pca the iris dataset contains four attributes per flower with the previous codewe would project it into three-dimensional space while keeping the relative distances between the individual flowers as much as possible in the previous examplewe did not specify any metricso mds will default to euclidean this means that flowers that were different according to their four attributes should also be far away in the mds-scaled three-dimensional spaceand flowers that were similar should be near together nowas shown in the following screenshotdoing the dimensional reduction to three and two dimensions with pca insteadwe see the expected bigger spread of the flowers belonging to the same classas shown in the following screenshot