Suggest method
That does not sound like a clustering problem at all since you already know the desired characteristics and are not trying to discover structure in your data. Simply define a score as a suitably weighted sum of individual features, order your passengers by that score, and pick the top few, or any that exceed a threshold etc. Not really an R problem at this point though. B.
On Apr 22, 2015, at 12:54 AM, Lalitha Kristipati <Lalitha.Kristipati at techmahindra.com> wrote:
Hi, I want to do a use case in R language. My problem statement is to upgrade the passengers from one membership level to another membership level in airlines based on their characteristics. It is like customer profiling based on their usage characteristics. Suggest a method that intakes a large amount of data and cluster them based on their characteristics and helps in knowing the passengers who are upgraded to another level . Any help is appreciated. Regards, Lalitha Kristipati Associate Software Engineer ============================================================================================================================ Disclaimer: This message and the information contained herein is proprietary and confidential and subject to the Tech Mahindra policy statement, you may review the policy at http://www.techmahindra.com/Disclaimer.html externally http://tim.techmahindra.com/tim/disclaimer.html internally within TechMahindra. ============================================================================================================================ [[alternative HTML version deleted]]
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