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 linechart). 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

Maybe you need a clustering algorithm?

Quoting from the link:

Cluster analysis or clustering is the
assignment of a set of observations
into subsets (called clusters) so that
observations in the same cluster are
similar in some sense. Clustering is a
method of unsupervised learning, and a
common technique for statistical data
analysis used in many fields