Mixed Euclidean Distance (Distance Metrics)

Question

Hi,

Rapidminer offers  "mixed Euclidean Distance" (MED) as distance measure. In contrast to the other distance measures 
I can not find MED as technical term in the text books and internet ressources available to me. I' d like to ask where I can find a reference which explains the computaion of this metric. Or does it refer to Euclidean Distance for datasets with mixed discrete and continuous variables?

Best

Norbert

MariusHelf · Answer

You are right.
Almost all distance measures do not normalize the data automatically.

Best regards,
Marius

kostanski · Answer

It is worth quota the full comment in the code of this class:

Euclidean distance for numerical and nominal values. For nomimal values, a distance of one is accounted if both values are not the same. Note: In most cases, you must normalize the numerical values, to obtain sound results.

So I understand, that it DOES NOT calculate normalized distance by default. If I am wrong, let me know.

steffen · Answer

Yes !

Quote the Java class: Euclidean distance for numerical and nominal values. For nomimal values, a distance of one is accounted if both values are not the same.