Introduction
Intuitive partitioning or natural partitioning is used in data discretization. Data discretization is the process of converting continuous values of an attribute into categorical data or partitions or intervals. This helps reducing data size by reducing number of possible values, so instead of storing every observation, we store partition range in which each observation falls. One of the easiest ways to partition numeric values is using intuitive (natural) partitioning.
Intuitive partitioning for data discretization
If an interval covers 3, 6, 7 or 9 distinct values at most significant digit, then create 3 intervals. Here, there can be 3 equal width intervals for 3, 6,

when low = -10.9 and high = 89, we get the range as -20 to 90, which covers 11 different values at MSD? or 10? Which category does this fall into? Certainly not the third one.

Hi Kaushal!

If we assume the range to be -20 to 90, we get 90- (-20) = 110, where MSD is 1. So rule 3 applies which says you should go for 5 partitions.

Partitions are:

[-20, 2]

(2, 24]

(24, 46]

(46, 68]

(68, 90]

P.S. Feel free to ask further questions. Questions related to other topics in data mining are also welcome at: ask (at) idevji.com.