Oct
7
Analysis of Tableau's Multi-Variable Clustering Algorithm
Following previous post on Iris Classification via Clustering in Tableau, we are going to analyse and compare the quality of clustering in Tableau by using 1,2,3 and 4 variables based on the Iris data set. We will use both automatic clustering and pre-specified number of clusters.
In the Iris data set, we know there are 3 clusters or classes of flowers. In some of the cases with a combination of measures/variables, Tableau can figure out automatically there are 3 clusters. We don't need to tell it a priori. In other cases, Tableau will find more or less than 3 by automatic clustering. Then in order to compare with all others, we will pre-specify the number of clusters to be 3.
In the Iris data set, we know there are 3 clusters or classes of flowers. In some of the cases with a combination of measures/variables, Tableau can figure out automatically there are 3 clusters. We don't need to tell it a priori. In other cases, Tableau will find more or less than 3 by automatic clustering. Then in order to compare with all others, we will pre-specify the number of clusters to be 3.
