CLUSTERING MADE EASY

Well since the day we started with Business Analytics lot of stress has been put on Clustering Technique. Well I pondered upon a number of websites to get an understanding of the same. The simplest definition that I came across is 

“Organizing data into classes such that there is

• High intra-class similarity
• Low inter-class similarity 

It is also known as classification by Statisticians and Segmentation by Marketers .


Let’s try to understand with the use of following illustrations.


What is a natural grouping among these objects ?

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Clustering is Subjective 

During Clustering we also came across one concept of Distance Measurement.

Definition: Let O1 and O2 be two objects from the universe of possible objects. The distance (dissimilarity) between O1 and O2 is a real number denoted by D(O1,O2) 

E.g. Let’s try to figure out dissimilarity in the following objects 

The Black box above comprises of a function which has the following properties 

• D(A,B) = D(B,A)         Symmetry 
• D(A,A) = 0         Constancy of Self-Similarity 
• D(A,B) = 0 If A= B Positivity (Separation)
• D(A,B) £ D(A,C) + D(B,C) Triangular Inequality 

Group : Marketing Group 5

Author of the Article: Navdeep Kumar

Roll no : 13150