Complex Network Analysis in Python

Choose the Right Distance

All similarity measures are numeric (usually on the scale from -1 to 1 or 0 to 1), so you must quantify any qualitative attributes before calculating similarities. Once quantified, the attributes can be thought of as coordinates of the object in a multidimensional coordinate space, where the number of dimensions equals the number of attributes. You can treat an object as a point in space, whose position is defined by the attributes. The similarity between two objects and the distance between the points representing the objects are complementary; the higher the distance, the smaller the similarity and vice versa.

Let’s now have a look at some typical distance and similarity measures.

Hamming Distance

Let’s suppose ...