What does this cluster plot explain?

My initial review of the plot shows that your cluster model isn't that great. I think you're suffering from a scaling issue because all other attributes look very flat. Try rescaling all the values (maybe use a Normalize operator with z-transformation) .The only thing that jumps out at me is that Cluster 3's basal volume is very different from all the rest. 

Yes that is true, I already am aware tha ty data need noralization but you could you please tell me what does this plot explain?? How can I interprete it? is it just saying that my clustering was done using only 3 three attributes? and is it showing only maximum attribute in each cluster or is it basd on the average ? 

Thank you

Hi,

No.  Each line in the plot shows the values of the centroid of your clusters.  Think about how k-means (and other centroid-based clustering mechanisms) work.  They determine the centroids for each of the k clusters and assign all data points to their nearest centroids.  In this sense the centroids can be seen as prototypical for your clusters.

The plot now shows for all your columns (in a so-called "parallel plot") where those cluster centroids are located.  This allows you to understand things like

1. where do the clusters differ most (which attributes are important for which cluster)
2. where do the clusters not differ (all clusters have basically the same values for certain attributes)
3. how "complex" are the differences between the clusters, i.e. do you need a lot of attributes to differentiate the clusters or only a few

Hope this helps,

Ingo

To tack on here, if I have z-score normalized a value like "Duration" in my Example Set, and the centroid value gets calculated as "- 0.5" in Cluster 1, does this indicate that centroid value for Duration in Cluster 1 is 0.5 of a standard score to the left (or less than the mean)?