Algorithm to generate numerical concept hierarchy

Question

I have a couple of numerical datasets that I need to create a concept hierarchy for. For now, I have been doing this manually by observing the data (and a corresponding line chart). Based on my intuition, I created some acceptable hierarchies.

This seems like a task that can be automated. Does anyone know if there is an algorithm to generate a concept hierarchy for numerical data?

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To give an example, I have the following dataset:

Bangladesh 521 

Brazil 8295 

Burma 446 

China 3259 

Congo 2952 

Egypt 2162 

Ethiopia 333 

France 46037 

Germany 44729 

India 1017 

Indonesia 2239 

Iran 4600 

Italy 38996 

Japan 38457 

Mexico 10200 

Nigeria 1401 

Pakistan 1022 

Philippines 1845 

Russia 11807 

South Africa 5685 

Thailand 4116 

Turkey 10479 

UK 43734 

US 47440 

Vietnam 1042

for which I created the following hierarchy:

• LOWEST ( < 1000)

• LOW (1000 - 2500)

• MEDIUM (2501 - 7500)

• HIGH (7501 - 30000)

• HIGHEST ( > 30000)

Answer 1

I think you're looking for something akin to data discretization that's fairly common in AI to convert continuous data (or discrete data with such a large number of classes as to be unwieldy) into discrete classes.