Hi,
I have built a Clustering model that captures customer demographic information
and identify various hidden clusters based on the information.
What kind of predictions can I make using the above model?
You can do multiple types of queries with a clustering model:
Get the most likely cluster for each case (or a new singleton case) - SELECT Cluster() FROM [model]|||
Thanks Raman,
The 1st, 2nd and the 4th points are clear but I have certain doubts
regarding the 3rd point you mentioned
Firstly as the attributes are customer characteristics like
age, gender and other demographic information and we suppose that the values
for these always exist for all the cases (new/old). What will be the point of
making them predictable and predicting their values again.
Secondly if I want to predict an attribute(s) like
MovieBuyer (determines whether a customer has bought a movie(s) or no) for new
cases, wouldn’t it be better if I use ‘decision trees’ or ‘neural networks’
algorithm rather than clustering.
Basically I cannot imagine a scenario in which clustering
stands out as the best suited algorithm for prediction.
It seems that Clustering is best suited for exploring and
understanding the data rather than for prediction.
I hope I have expressed my problem adequately and clearly.
Any help would be most appreciated.
|||Your assessment is correct in that clustering is more suitable for data exploration/understanding - I was just pointing out that it is *possible* to do prediction with the SQL Server DM Clustering algorithm (which was your original question).
|||Thanks ramansql
